Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 17th May 2022, 05:26:39 CEST

 
 
Session Overview
Date: Tuesday, 31/Aug/2021
8:00 - 9:00Opening registration desk
Location: Cityhall (Belfry)

The registration desk will open at 08:00, and will remain open until 19:30.

Cityhall (Belfry) 
9:00 - 10:30Workshop 2: Urban Energy Lab 4.0 - An integrated step towards a sustainable future of city districts
Location: Cityhall (Belfry) - Room 1
Session Chair: Christian Vering, RWTH Aachen University
Session Chair: Dirk Müller, RWTH Aachen
Cityhall (Belfry) - Room 1 
 

Urban Energy Lab 4.0 - An integrated step towards a sustainable future of city districts

Christian Vering, Rita Streblow, Dirk Müller

RWTH Aachen University, Germany

 
10:30 - 12:30Workshop 4: Introduction to statistical learning - application to building energy data analysis
Location: Cityhall (Belfry) - Room 4
Session Chair: Simon Rouchier, Université Savoie Mont Blanc
Cityhall (Belfry) - Room 4 
 

Introduction to statistical learning - application to building energy data analysis

Simon Rouchier

Université Savoie Mont Blanc, France

 
11:00 - 12:30Workshop 3: SIM-VICUS - A new and open source approach for dynamic Building Energy Performance Simulation
Location: Virtual Meeting Room 1
Session Chair: Stephan Hirth, TU Dresden
Virtual Meeting Room 1 
 

The novel dynamic building energy performance simulation tool SIM-VICUS

Stephan Hirth, Andreas Nicolai

TU Dresden, Germany

 
13:30 - 17:00Workshop 1: Introduction to the BOPTEST framework for simulation-based benchmarking of advanced controllers
Location: Cityhall (Belfry) - Room 1
Session Chair: Javier Arroyo, KU Leuven
Cityhall (Belfry) - Room 1 
 

Introduction to the BOPTEST framework for simulation-based benchmarking of advanced controllers

Javier Arroyo1,2,3, David Blum4

1Department of Mechanical Engineering, KU Leuven, Heverlee, Belgium; 2EnergyVille, Thor Park, Waterschei, Belgium; 3Flemish Institute for Technological Research (VITO), Mol, Belgium; 4Lawrence Berkeley National Laboratory, Berkeley, USA

 
14:00 - 17:00Technical tour: Lam Gods: Technical tour: Lam Gods
Location: Sint-Baafs Cathedral
Sint-Baafs Cathedral 
19:30 - 20:15Keynote Ardeshir Mahdavi - The Sound of Space: Reflections on Architecture, Acoustics, and Music
Location: Cityhall (Belfry)
Session Chair: Dirk Saelens, KU Leuven / EnergyVille
Cityhall (Belfry) 
20:15 - 20:45Awarding Ceremony for the winner of the Music Competition
Location: Cityhall (Belfry)
Session Chair: Dirk Saelens, KU Leuven / EnergyVille

Frank Deleu will talk about the Carillon at the Belfry.

Awarding ceremony for the winner of the music competition.

Wim Berteloot will play the winning composition on the Carillon.

Cityhall (Belfry) 
20:45 - 22:00Welcome Reception
Location: Cityhall (Belfry)

 

Cityhall (Belfry) 
Date: Wednesday, 01/Sept/2021
7:00 - 8:30Opening registration desk
Location: Concert Hall

The registration desk will open at 07:00, and will remain open until 20:00.

Concert Hall 
8:30 - 9:00Plenary Opening Ceremony
Location: Concert Hall - Concertzaal

Chairs: Lieve Helsen, KU Leuven / Energyville and Wim Boydens, boydens engineering, part of Sweco / Ghent University

Conference Opening - Food for thoughts

IBPSA and IBPSA NVL Welcome words (Lori McElroy and Dirk Saelens)

Opening Innovation Speech by Minister of Innovation Hilde Crevits

Concert Hall - Concertzaal 
9:00 - 9:15Keynote: Thoughts of leading Industry by Martin Dieryckx, General Manager Environmental Research Center Daikin Europe
Location: Concert Hall - Concertzaal
Concert Hall - Concertzaal 
9:15 - 10:00Keynote: Climate Change, The European Green Deal and the Building sector by Jos Delbeke - former Director-General of the European Commission's DG Climate Action
Location: Concert Hall - Concertzaal
Concert Hall - Concertzaal 
10:00 - 10:30Coffee Break
Location: Concert Hall - Foyers
Concert Hall - Foyers 
10:30 - 12:00Session W1.1: Practice and industry related case studies
Location: Concert Hall - Forum 6
Session Chair: Mathias Bouquerel, EDF R&D
Session Chair: Thomas Bockelandt, Boydens engineering
Concert Hall - Forum 6 
 
10:30 - 10:48

A BIM-based Business Process Model to support LEED® certification in retrofit projects.

Letizia D'Angelo1,2,3, Magdalena Hajdukiewicz1,2,3, Federico Seri1,2,3, Marcus Keane1,2,3

1School of Engineering, College of Science and Engineering, National University of Ireland, Galway; 2Informatics Research Unit for Sustainable Engineering (IRUSE), National University of Ireland Galway; 3Ryan Institute, National University of Ireland Galway

Aim and Approach

(max 200 words)

Energy efficiency plays a vital role in reducing the impact of the buildings’ energy costs and avoid greenhouse gas emissions, but the global rate of progress is slowing.

The aim of the EU's Energy Efficiency Directive (EED) is to help citizens and public authorities to better manage their energy consumption. If successful, this will bridge the gap between existing framework directives and national energy efficiency measures.

Within this objective, the LEED certifications may improve the achievement of these results. In fact, LEED certified buildings not only increase the building efficiency, they also add value to the properties and represent an ethical system for sustainability. Furthermore, those certified buildings can qualify for discounted insurance, tax breaks and other incentives.

In this paper, the LEED process will be analysed utilising a methodological approach aimed at defining an innovative Business Process Model (BPM) using the benefits of the BIM.

Scientific Innovation and Relevance

(max 200 words)

The advantages of using a detailed BIM Project Execution Plan (BEP) are well recognised in the marketing sector for achieving a high-quality sustainability rating in a short period of time, but both a planning guide and the benefits have only been demonstrated in new construction projects.

The aim of this research is to create a business process model (BPM) that clearly underline the workflow of retrofitting existing buildings using the benefit of BIM.

In a renovation projects there are many use cases of BIM that have to be considered in the process such as the existing conditions modeling (enhance the accuracy of existing conditions documentation), cost estimation (cost effects of additions and modifications), energy analysis (increase efficiency of structural, electrical and mechanical system) and so on.

This paper will focus on increasing the effectiveness of sustainability goals, the LEED evaluation, so the detailed process map (BPM) of this BIM use has been carried out using the Business Process Modeling and Notations (BPMN) v2.0, an established modeling language able to graphically represent the overall process.

Preliminary Results and Conclusions

(max 200 words)

This research presents an innovative methodological approach aimed at defining a novel BIM based BPM for the acquisition of the credit “Optimize Energy Performance” in the process of a LEED certification for an existing building.

A thermal model of the building “as is” (baseline) has been created using the software IES-VE and has been compared with its retrofitted scenario (proposed). After the insulation of the envelope and the combined use of a more efficient heating/cooling system and renewable sources such as a new photovoltaic system and solar panels the percent savings of the energy use has been the 64%, reaching 18 points out of 18.

Main References

(max 200 words)

(1) “BIM Project Execution Planning Guide – Version 2.0.” April 16, 2010 The Pennsylvania State University, University Park, PA, USA

(2) ASHRAE (2019) ASHRAE Standard 90.1 - Energy Standard for Buildings Except Low-Rise Residential Buildings.

(3) Building Certification: What Does LEED Really Mean? Available at: https://dfw.cbslocal.com/2013/04/10/building-certification-what-does-leed-really-mean/.

(4) D’Angelo, L. et al. (2019) ‘BIM-based Business Process Model to support systematic deep renovation of buildings" doi:10.26868/25222708.2019.210481

(5) LEED, Reference guide for Buidling Design and Construction (2014), U.S. Green Building Council



10:48 - 11:06

Ecological and economic analysis of low-temperature district heating in typical residential areas

Jan Stock1, Dominik Hering1, André Xhonneux1, Dirk Müller1,2

1Forschungszentrum Jülich GmbH, Institute of Energy and Climate Research, Energy Systems Engineering (IEK-10), Jülich, Germany; 2RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, Aachen, Germany

Aim and Approach

(max 200 words)

District heating is a key heating supply technology for the building sector. Decreasing the operation temperatures of district heating allows to increase efficiency and to use new sources of heat, such as low temperature waste heat or sustainable energy sources. Low-temperatures district heating networks, also known as district heating networks of the fourth generation, have operation temperatures up to 60°C. [1]

The aim of this investigation is to compare low-temperature district heating for typical residential areas.

We use typical building types and characteristics of typical residential areas in Germany to create dynamic simulation models in MODELICA [2,3]. Based on the simulation results, we evaluate installation and operating costs relative to supplied heat.

We conclude the ecologic and economic investigations with a classification of the most efficient low-temperature district heating integrations in the investigated residential areas.

Scientific Innovation and Relevance

(max 200 words)

Successful heat supply with low-temperature district heating already has been shown for old and modern building types [4,5]. An efficient integration of low-temperature district heating depends on the supplied building types and their specific heat demands and temperature requirements [6].

We present an investigation of typical residential areas with varying building size and age. We use typical building types of the German building stock and combine them to typical residential areas. We use open-source Python tools for automated model generation, which allows us to create multiple dynamic simulation models [7]. For this evaluation, we investigate nine typical residential areas with varying characteristics.

With the results of this investigation, we show the most efficient and beneficial use of a low temperature heating source for building heating supply.

Preliminary Results and Conclusions

(max 200 words)

The results show that an efficient heat supply depends on different building specifications. A network with a 40°C heat source can efficiently supply residential areas with many modern single-family houses. Especially a high amount of direct heat by the network and a high space heating share leads to an efficient use of supplied heat. With a 60°C low-temperature district heating network housing areas with a high number of old buildings can be supplied efficiently. In contrast to that, the supply of a residential area with many modern multi-family houses needs a big amount of additional electricity for heat pump operation to support high temperature requirements. Reference scenarios with air source heat pumps show a higher primary energy consumption than the supply with low-temperature district heating. The cost evaluation of the low-temperature district heating scenarios shows that residential areas with a high heat density have the smallest specific investment costs refer to possible primary energy saving.

Main References

(max 200 words)

[1] Lund et al.: 4th Generation District Heating (4GDH). In: Energy 68 (2014), S. 1–11

[2] Loga et al.: Deutsche Wohngebäudetypologie: Beispielhafte Maßnahmen zur Verbesserung der Energieeffizienz von typischen Wohngebäuden ; erarbeitet im Rahmen der EU-Projekte TABULA - "Typology approach for building stock energy assessment". 2., erw. Aufl. Darmstadt : IWU, 2015 http://www.building-typology.eu/downloads/public/docs/brochure/DE_TABULA_TypologyBrochure_IWU.pdf.

– ISBN 9783941140479

[3] Remmen et al.: TEASER: an open tool for urban energy modelling of building

stocks. In: Journal of Building Performance Simulation 11 (2018), Nr. 1, S. 84–98

[4] Brand et al.: Renewable-based low-temperature district heating for existing buildings in various stages of refurbishment. In: Energy 62 (2013), S. 311–319

[5] Schmidtet al.: Development of an Innovative Low Temperature Heat Supply Concept for a New Housing Area. In: Energy Procedia 116 (2017), S. 39–47

[6] Köfinger et al.: Low temperature district heating in Austria: Energetic, ecologic and

economic comparison of four case studies. In: Energy 110 (2016), S. 95–104

[7] Fuchs et al.: Workflow automation for combined modeling of buildings and

district energy systems. In: Energy 117 (2016), S. 478–484



11:06 - 11:24

Multidisciplinary BIM-model for an integrative design approach: study case of a car dealership building in Brussels

Nassim Jamali, Pedro Marques, Jolien De Clerck, Wim Boydens

Boydens Engineering, Belgium

Aim and Approach

(max 200 words)

Elaboration of BIM model permitting a holistic approach of the MEP design.

The automation of workflow enables the increase of iteration of simulations. This leads to high quality optimization of the design.

Scientific Innovation and Relevance

(max 200 words)

• Multidisciplinary approach on MEP design

• Translation from BIM to BEM and other models

• Integrative design using simulations from early-stage

Preliminary Results and Conclusions

(max 200 words)

The iterations of the design brought the project to be Net Zero Energy Building and Carbon Neutral.

Main References

(max 200 words)

Boydens Standards



11:24 - 11:42

Facility location problem in thermal network design

Tristan André Rey, Jessen Page

HES-SO, Switzerland

Aim and Approach

(max 200 words)

Energy transition requires efficient energy production and distribution systems. For this purpose, a methodology is developed to extract the energy of ground water and to distribute it optimally in a neighborhood.The first step of the methodology consists in the geographical clustering of the buildings, aiming to reduce the complexity of the problem. Then, knowing the energy demand of the neighborhood and potential locations for ground water wells, the resolution of an assignment problem (capacitated facility location splittable problem - CFLS problem) is performed. Each ground water well can be drilled or not and has a specific amount of power available. The goal of the resolution is then to determine which drillings need be executed and which buildings they should supply, while minimizing the total cost of the operation. To do so, this assignment problem is solved using a bespoke solving method and the results are compared to those obtained with a mixed-integer linear programming (MILP) based solving method. The methodology ends with the design of the topology of a thermal network. This design process uses street network data and is based on the resolution of a minimum Steiner tree.

Scientific Innovation and Relevance

(max 200 words)

The temperature increase associated to climate change implies an increasing demand for cooling. This demand needs to be fulfilled in an efficient way and the use of ground water for this purpose becomes more frequent. Ground water can be used for heating or cooling and is thus of prime interest for district networks. However, the introduction of multiple sources complexifies the design process. The resolution of the CFLS problem is well-known by the optimization and operational research community and is applied here to the design of thermal networks, as it meets the expectations required for these designs.

Preliminary Results and Conclusions

(max 200 words)

The applicability of the methodology is validated with a case study. The bespoke solving method generates multiple solutions using a heuristic algorithm while the MILP based solving method generates multiple solutions by the way of integer cuts. Key performance indicators (KPIs) are implemented and an a priori optimal solution is chosen using parallel coordinates for a multi-criterion based decision.

Main References

(max 200 words)

- Madhukar R. Korupolu, C. Greg Plaxton, and Rajmohan Rajaraman. “Analysis of a Local Search Heuristic for Facility Location Problems”. In: Journal of Algorithms 37 (2000), pp. 146-188

- Stéphane Joos, François Maréchal, Jérémy Unternährer, Stefano Moret. “Spatial clustering for district heating integration in urban energy systems: application to geothermal energy”. In: Applied energy (2016)

- Luc Girardin, “A GIS-based Methodology for the Evaluation of Integrated Energy Systems in Urban Area”. EPFL, 2012



11:42 - 12:00

MILP based approach for the preliminary investigation of thermal networks in urban areas

Francesca Belfiore1,2, Tristan Rey1, Jessen Page1, François Maréchal2

1HES-SO Valais-Wallis, Switzerland; 2École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

Aim and Approach

(max 200 words)

Distric Energy Systems (DES) have been widely recognized as crucial actors during the ongoing Energy Transition, demanded by the challenging mid-century emission reduction target. While district heating still represents the most common type of DES, the so-called “anergy network” allows to exploit synergies between heating and cooling sectors representing a promising opportunity to improve energy efficiency in urban areas. In this framework, this study aims at proposing cost optimal solutions for the design and operation of a DES in a neighborhood characterized by a variegate building stock, per year of construction and dwelling affectation. In particular different network types (heating, cooling and anergy) are investigated together with the resulting degree of centralization and respectively decentralization of heat and cold production. The problem is formulated as a Mixed Integer Linear Programming (MILP), with binary variables linked to the selection and scheduling of technologies as well as the existence and type of pipelines, while continuous variables are associated to sizes and operating loads. A set of potential solutions is generated by the means of integer cut constraints on the network design. The impact of the users temperature on the system design is also investigated.

Scientific Innovation and Relevance

(max 200 words)

Distric Energy System (DES) represents a promising opportunity to boost the decarbonisation of the urban sector, promoting system electrification and the integration of more sustainable technologies. To fully exploit the benefits of DES all the components involved in the district must be optimized, from the heat source to the final users, including the distribution network. However, the optimization of such complex systems is a challenging tasks for several reasons: it includes both spatial and temporal aspects, consumption profiles may vary in stochastic manner and it involves a large number of decision variables, both continuous and binaries. This works proposes a MILP framework to investigate different types of networks within the district and the interaction with the energy system at the building level. Both temporal and spatial clustering are employed to reduce the problem size. The network temperature, often assumed constant during a summer/winter operation is also subject to optimization, with either a constant profile or a linear trend with the ambient temperature. Two different approaches to optimize the network temperature levels are compared: the use of a heuristic master level optimization and an integer cut-constraint applied to the MILP.

Preliminary Results and Conclusions

(max 200 words)

Preliminary results show the crucial role of optimization in defining optimum solutions among the many available options: an anergy network coupled with decentralized heat pumps and electrically driven vapour compression chillers, a heating network whose temperature level implies a certain degree of decentralization of heat production and eventually a cooling network. The distribution of the temperature demand among the users, resulting from the diversity of the building stock also affects the set of optimal solutions, suggesting the importance of considering building refurbishment options among the decision variables. Due to the large capital investment of network pipeline, operational constraints such as the maximum allowed velocity play also a role in identifying the cost optimal solutions. In the case of a partially decentralized heating network the overall system efficiency is linked to the coefficient of performance of the central and decentralized heat pumps and the homogeneity of the temperature demanded by the different buildings.

Main References

(max 200 words)

REN21. 2020. Renewables 2020 Global Status Report (Paris: REN21 Secretariat). ISBN 978-3-948393-00-7.

IEA (2019). The Critical Role of Buildings. (Paris IEA).

5th generation district heating and cooling systems: A review of existing cases in Europe. Buffa et al. Renewable and Sustainable Energy Reviews, April 2019.

Distributed or centralized? Designing district-level urban energy systems by a hierarchical approach considering demand uncertainties. R. Jing at al. Applied Energy, vol 252, October 2019.

4th Generation District Heating (4GDH): Integrating smart thermal grids into future sustainable energy systems. H. Lund et al. Energy, vol. 68, no. Supplement C, pp. 1–11, Apr. 2014.

Multi-objective, multi-period optimization of district energy systems: Networks design. S. Fazlollahi et al. Computer Aided Chemical Engineering, ser. 23 European Symposium on Computer Aided Process Engineering.

MIP approach for designing heating systems in residential buildings and neighbourhoods. H. Harb at al. Journal of Building Performance Simulation, vol. 9, no. 3, pp. 316–330, May 2016. Available: https://doi.org/10.1080/19401493.2015.1051113

Performance and profitability perspectives of a CO2 based district energy network in Geneva's City Centre. S. Henchoz at al. Energy, vol 85, June 2015.

 
10:30 - 12:00Session W1.2: Student Modelling Competition: Can we build a building without HVAC and achieve good comfort in Belgium (like 2226 in Austria)?
Location: Concert Hall - Artiestenfoyer
Session Chair: Elisa Van Kenhove, Ghent University

The aim of the student modelling challenge & competition is to facilitate wider participation in the conference by providing a competitive forum for MSc and PhD students to explore the use of building performance simulation.

In this special edition of the IBPSA student challenge & competition, we have encouraged participants to use the IBPSA network to share information, ask questions and provide solutions as well as to collaborate and learn from each other. The subject of the study is the low-tech building 2226 of Baumslager & Eberle in Lustenau. Out of all participating teams, two finalists are selected that will present their work in this session.

20 minutes: Presentation of finalist 1: Bergische Universität Wuppertal, Germany

  • Karl Walther
  • Isıl Kalpkirmaz Rizaoglu
  • Hale Tugçin Kirant-Mitic
  • Ghadeer Derbas

 20 minutes: Presentation of finalist 2: CEPT University, India

  • Divya Mullick
  • Priyanka K Raman
  • Sakshi Nathani
  • Shivangi Singh
  • Shreya Nigam
  • Sujitha Subbiah

Questions from student modelling competition panel and audience.

Concert Hall - Artiestenfoyer 
10:30 - 12:00Session W1.3: Buildings paving the way for the energy transition
Location: Concert Hall - Studio 1
Session Chair: Wilfried GJHM van Sark, Utrecht University
Session Chair: Eric Deen, Viessmann
Concert Hall - Studio 1 
 
10:30 - 10:48

MUSEGRIDS tool: energy performance calculation based on EPBD standards for EU and abroad

Gema Hernández Moral, Victor Iván Serna González, Francisco Javier Miguel, César Valmaseda Tranque

Fundacion CARTIF, Spain

Aim and Approach

(max 200 words)

The implementation of energy policies with a view to reduce CO2 emissions poses specific challenges, especially to public authorities, who should define specific objectives, and evaluate the adequacy and impact of energy actions proposed. Nevertheless, an appropriate analysis is highly time-consuming due to the lack of tools. In this process, the first step is to establish the baseline energy status of the area of study. Only with this knowledge, in particular of the residential sector (main CO2 emissions contributor in cities), is it possible to plan for a low carbon economy. In this context, the MUSEGRIDS tool will support energy planners by matching energy needs to energy supply of the building stock at local scale. In this paper, the first step of the approach is explained: the attainment of the energy demand. This is calculated at building level, but then aggregated at other scales. To do so, publicly available data sources, building typologies (such as those coming from TABULA or the Building Stock Observatory), and reference data coming from Open Street Maps and INSPIRE-based data are deployed. This allows to automatically calculate hourly energy demand and consumption values based on the ISO 52000 standards family.

Scientific Innovation and Relevance

(max 200 words)

By basing the proposed tool on Energy Performance Certificates (EPC) calculation standards specified in the Energy Performance Directive of Buildings (EPBD 2018/844/EU), in particular ISO 52016; the MUSEGRIDS tool achieves two main goals: it aids in the implementation of energy directives and energy actions by offering an easy to use tool to identify areas in need and, secondly, it promotes the EPBD, by making use of one of its main instruments to measure energy performance. The energy performance of buildings is calculated at a building scale, but then aggregated at coarser levels of detail, in order to enable different actors to complement their decision-making process in the most appropriate way. This is performed by exploiting publicly available data (from building typologies, open street maps or based on the INSPIRE Directive). Thus, based on this accessible-to-all approach it is argued how it could be replicated in a European context, as well as in a global context, and how the input data can be more or less accurate depending on this scope.

Preliminary Results and Conclusions

(max 200 words)

The developed tool provides three main outputs: (1) GIS file with geo-located information for each building of a municipality in terms of energy needs (cooling and heating demand), DHW, energy per type of fuel, CO2 emissions per year; (2) the same information aggregated for all the building but disaggregated by time (per hour); (3) raster files with the same information mapped in a 100x100m2 grid.

The tool has been evaluated and validated in different ways, and tested in three locations: Osimo (IT), Oud-Heverlee (BE) and Aranda de Duero (ES). In this process, failures in the combination of data sources, mapping, calculation process have been detected and also the accuracy of the results tested based on the comparison with real data.

All in all, even when the tool has the ambition to be applied worldwide, the main barrier is the lack of completeness in the source data: both in terms of geometric and buildings identification data (from OSM and INSPIRE-based) or building characterisation data (e.g in Tabula-episcope for some countries or regions). The systematic and harmonised characterisation of buildings and their typologies would highly benefit this process and contribute to more robust decision-making in the field of energy performance in buildings.

Main References

(max 200 words)

Directive 2018/844/EU. European Parliament and the Council of 30 May 2018 “On the Energy Performance of Buildings”:https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=uriserv%3AOJ.L_.2018.156.01.0075.01.ENG[retrieved: Jul, 2020]

Howard B, Parshall L, Thompson J, Hammer S, Dickinson J and Modi V 2012 Spatial distribution of urban building energy consumption by end useEnergy Build.45 141–51

Kavgic M, Mavrogianni A, Mumovic D, Summerfield A, Stevanovic Z and Djurovic-PetrovicM 2010 A review of bottom-up building stock models for energy consumption in the residential sectorBuild. Environ.45 1683–97

Directive (2007/2/EC) establishing an Infrastructure for Spatial Information in the European Community (INSPIRE): https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX%3A32007L0002 [retrieved: Jul, 2020]

Miranda Pereira I and Sad de Assis E 2013 Urban energy consumption mapping for energy management Energy Policy59257–69



10:48 - 11:06

Optimal operation of distributed energy systems - a game theory based approach

Sarah Henn, Sarah Welter, Tanja Osterhage, Dirk Müller

RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, Germany

Aim and Approach

(max 200 words)

Within the ongoing transformation of the energy system, we observe a number of key drivers that require a conversion to localized energy system operation solutions [1]. On the one hand, there is an increase of distributed energy resources and a higher demand of electricity due to electrification of mobility and heating sector. On the other hand, there are limited distribution grid capacities.

These factors lead to a growing need for flexibilization of energy demand, for instance by intelligently operated energy storage systems as well as district or building energy systems. Local energy systems must be managed by means of a whole system approach, which is robust and allows for interconnecting localized solutions [2]. Moreover, it is necessary that this solution is able to deal with competing requirements on limited resources.

This study aims to evolve a solution, fitting all these requirements, by using a game theory based approach. Distributed coordination relying on game theoretic principles allows for an interconnected, autonomous and non-discriminatory operation. Within the study we evolve a game theoretic approach and simulatively apply it to a residential neighbourhood. We compare the consequential building energy system operation to both central and a fully decentral operation optimization.

Scientific Innovation and Relevance

(max 200 words)

Current literature reviews on optimal district operation treat game theory as a promising approach in local energy trading [1] [3]. Reynolds states that “the autonomous, distributed, and heterogeneous nature of the smart grid make game theory well suited to smart grid problems” [2].

However, many studies investigated either load or feed-in situations. As neighbourhoods of the future will certainly have to meet both requirements, we introduce an approach which tackles both. Furthermore, numerous studies compared the game theoretic operation to an operation without usage of flexibilities, e.g. [4], [5] and [6]. A comparison with intelligent alternative approaches of operation was rarely made, e.g. in [7].

In our game-theory approach, the households of a district play a dynamic non-cooperative game in order to find their optimal energy consumption and feed-in schedule, as e.g. in [8]. Therefore, the players act in a continuous strategy space, optimizing their pay-off with limited information of the trading behaviors of their peers. We derive the closed-form expression of the best response by means of the adjusted, above described MILP sub problems. Thus, the Nash-equilibrium of the whole game is calculated iteratively.

Preliminary Results and Conclusions

(max 200 words)

Our results showed that the game theoretic approach offers advantages only in terms of grid supportiveness, as high full-load hours are realized. With regard to costs, energy consumption, emissions and computing effort the compared approaches were preferable. Central coordination schemes were best in terms of self-consumption ratio, autarky ratio and hours of autonomy from the grid.

Even in the neighborhood surveyed, with homogeneous building types and homogeneous BES, there was a high potential for energy trading or sharing among the residents. This led to significantly lower costs for a cost balance regarding the whole neighbourhood instead of a balance by building. Thus, considering neighbourhoods as a whole system holds potential monetary savings for residents depending on the billing scheme as well as possibilities for future business models of energy suppliers and district operators.

Nevertheless, user privacy and autonomy should be compromised as minimally as possible when designing a neighborhood control system. Here, we believe that distributed approaches generally offer a favorable tradeoff between control performance and autonomy.

Main References

(max 200 words)

[1] Reynolds, J. (2019). Real-time and semantic energy management across buildings in a district configuration (Doctoral dissertation, Cardiff University).

[2] Zhou, Y., Wu, J., Long, C., & Ming, W. (2020). State-of-the-art analysis and perspectives for peer-to-peer energy trading. Engineering.

[3] Zia, M. F., Elbouchikhi, E., & Benbouzid, M. (2018). Microgrids energy management systems: A critical review on methods, solutions, and prospects. Applied energy, 222, 1033-1055.

[4] Witte, P. and M. Kaltschmitt (2017). Dezentrale Steuerung eines Pools von Wärmepumpen auf Basis spieltheoretischer Methoden. Zeitschrift für Energiewirtschaft 41 (4), 237-259.

[5] Pilz, M., L. Al-Fagih, and E. Pfuegel (2017). Energy Storage Scheduling with an Advanced Battery Model: A Game-Theoretic Approach. Inventions 2 (4), 30.

[6] Nguyen, H. K., J. B. Song, and Z. Han (2015). Distributed Demand Side Management with Energy Storage in Smart Grid. IEEE Transactions on Parallel and Distributed Systems 26 (12), 3346-3357.

[7] Yaagoubi, N. and H. T. Mouftah (2014). User-aware game theoretic approach for demand management. IEEE Transactions on Smart Grid 6 (2), 716-725.

[8] Pilz, M., & Al-Fagih, L. (2019). A dynamic game approach for demand-side management: scheduling energy storage with forecasting errors. Dynamic Games and Applications, 1-33.



11:06 - 11:24

Impact of 2-zone recirculation on IAQ and energy performance of a demand controlled MEV system

Ivan Pollet1, Bavo De Maré1, Steven Delrue1, Frederik Losfeld1, Jelle Laverge2, Samuel Caillou3

1Research, Renson Ventilation, Waregem, Belgium; 2Building Physics Research Group, Ghent University, Gent, Belgium; 3Belgian Building Research Institute (BBRI), Limelette, Belgium

Aim and Approach

(max 200 words)

Demand controlled mechanical extract ventilation (MEV) systems with natural air inlets and central mechanical ventilation systems with heat recovery (MVHR) are usually used in the Belgian residential sector to control IAQ. In order to balance the supply and extract air flow rates of MVHR systems, air can be transferred mechanically between habitable rooms to reduce the supply capacity of the unit, called a 2-zone recirculation or cascade system. A similar approach can be applied to balance MEV systems by transferring air from the night to the day zone, while reducing natural air supply. CONTAM simulations were performed on several residential models (without or with open kitchen, natural or mechanical indoor air transfers, with or without air supply in the living room) to analyze the impact on IAQ (CO2, RH) and energy efficiency EE (heating losses) of MEV systems.

Scientific Innovation and Relevance

(max 200 words)

Internationally, recirculation MEV systems were limited studied [1;2;3;4]. The performance depends mainly on the applied control strategy as a function of the dwelling structure. Especially in case of demand controlled MEV systems, a smart control of the indoor air transfer is crucial to guarantee the IAQ in all habitable rooms. The pollutants transferred from the night to the day zone have to be evacuated from the day zone, to prevent backflow to the night zone. Cascading also allows to limit the natural air supply in the day zone which affects the cross flows through the dwelling, and in that way the local IAQ and overall energy consumption. A MEV system with direct extraction from all rooms, functional as well as habitable ones, and air flow rates controlled on CO2, VOC or RH, was used as benchmark for IAQ and EE.

Preliminary Results and Conclusions

(max 200 words)

Preliminary results clearly prove that pollutants cannot be stored indoors, contrary to the storage of heat or cold. Pollutants can be transferred within the house, but finally have to be extracted to prevent unwanted backflow. The indoor air transfer can be carried out by means of ducts combined with a central transfer fan or by means of individual room transfer fans connected to the circulations spaces. The impact of both configurations on IAQ and EE is limited.

The cascade principle is promising in case of an open kitchen where the extraction is controlled on CO2 and RH to allow a free transfer between the living room and the kitchen. Due to no air supply vents in the living room/open kitchen, the extraction in the kitchen must be increased to maintain the same reference IAQ. The IAQ in the bedrooms is slightly worse, since door undercuts providing air supplied from the circulation spaces, were not available anymore. Further modelling and simulation research must allow to optimize the performance of a 2-zone recirculation MEV system to a full extraction MEV systems by optimizing the control strategies of the mechanical transfer devices in relation to the extract flows from the functional rooms.

Main References

(max 200 words)

[1] Rojas, G. (2015). Optimization Potentials for Mechanical Ventilation of Energy Efficient Housing - Simulation and Evaluation Methods. Thesis, 147 p. DOI: 10.13140/RG.2.1.4959.2404

[2] Rojas, G., Pfluger, R., Feist, W. (2015). Cascade ventilation – air exchange efficiency in living rooms without separate supply air. Energy and Buildings, 100, 27-33.

[3] Van Gaever, R., Laverge, J., Caillou, S. (2016). A comparison of different ventilation strategies for dwellings in terms of airflow rates and airflow paths. 14th Indoor Air Conference, Ghent, 3-8 July 2016, paper 786.

[4] Van Gaever, R., Caillou, S., Pecceu, S. (2019). Minimising the influence of the stack effect and wind on the operation of mechanical exhaust ventilation systems. 40th AIVC Conference, Ghent (Belgium), 15-16 October 2019, 263-271.



11:24 - 11:42

Global sensitivity analysis of a bottom-up building stock energy model

Sebastian Forthuber, Lukas Kranzl, Andreas Müller, Iná Maia

TU Wien, Austria

Aim and Approach

(max 200 words)

For various planning and policy issues the estimation of future

development of heating and cooling demand is of great importance.

However techono-socio-economic building stock energy models used for

energy and emission development projections and policy assessment

involve considerable uncertainty. In this paper we assess the building

stock model Invert/EE-Lab (www.invert.at), using the Elementary Effects

Method, a method appropriate for the degree of complexity of the model.

We provide exemplary results for selected parameters for selected

countries that have been acquired in the IEA EBC Annex 70 – Building

Energy Epidemiology project. Invert/EE-Lab is a dynamic bottom-up model

that evaluates the effects of economic and regulatory conditions on

future development of total energy demand, energy carrier mix, CO2

emission reduction and costs.The model builds on input data including a

disaggregated building stock database on country level, supply

technologies, regional climate, energy prices and energy carrier

potentials as well as behavioural aspects and investment decision

criteria. Within this article we focus on the analysis of the influence

of relevant indicators such as interest rates, costs, energy prices,

selected technical parameters and behavioural aspects on the final

energy demand, respectively related energy carrier shares or installed

capacities.

Scientific Innovation and Relevance

(max 200 words)

The Elementary Effects method can be seen as a randomized

“One-At-a-Time” design. Elementary effects for each input are computed

from different points in the input space, leading to to mean and

standard deviation that can be taken as a measure of importance of a

specific input variable and its interactions with other inputs. This

method is applied to the building stock model Invert/EE-Lab. The key

approach of the model Invert/EE-Lab is to describe the building stock,

heating, cooling and hot water systems on disaggregated level, calculate

related energy needs and delivered energy, determine reinvestment cycles

and new investment of building components and technologies. The core of

the tool is a myopical, multinominal logit approach, which optimizes

objectives of agents.

For the application of the EE-method to Invert/EE-Lab we use the SAFE

toolbox to generate the input samples used for the model iterations as

well as for analysis and visualization. The great variety of input

paramters was broken down to 11 parameters, comprising of interest

rates, different investment decision parameters, heating system and

renovation costs, energy prices, lifetime of buildings and heatpump

coefficient of performance, as well as factors representing user behaviour.

Preliminary Results and Conclusions

(max 200 words)

The analysis was carried out with respect to the output variables

installed capacity of heatpumps and share of final energy demand related

to heatpumps and natural gas heating systems. The results for installed

heatpump capacity show different levels of importance and

interconnections for the evaluated input variables. Whereas the

parameter economic weight can be considered to be of significant

influence and great interconnection with other variables, others like

interest rates, costs and behavioural factors can be considered as non

influential on the observed output variable. It has to be mentioned

tough, that the results are highly dependent on the selected value

ranges for the input parameters, as well as on country specific datasets

and presets. The results also provide confidence bounds and convergence

investigations which lead to differentiated analysis of the parameter

impacts. These is explained in more detail in the full paper. The

sensitivity analysis carried out through the Elementary effects method

provides valuable insights for the influence of various input

parameters. The insights gained can be used for improved scenario

development as well as deeper result interpretation trough better model

understanding.

Main References

(max 200 words)

Campolongo, F., S. Tarantola and A. Saltelli. (1999). "Tackling

quantitatively large dimensionality problems". Computer Physics

Communications. 1999 (1–2): 75–85. Bibcode:1999CoPhC.117...75C.

doi:10.1016/S0010-4655(98)00165-9.

Müller, A., 2015. Energy Demand Assessment for Space Conditioning and

Domestic Hot Water: A Case Study for the Austrian Building Stock

(PhD-Thesis). Technische Universität Wien, Wien.

Kranzl, L., Hummel, M., Müller, A., Steinbach, J., 2013. Renewable

heating: Perspectives and the impact of policy instruments. Energy

Policy. https://doi.org/10.1016/j.enpol.2013.03.050

Invert/EE-Lab [Model website], URL http://invert.at/ (accessed 4.4.17).

Morris, M.D., 1991. Factorial Sampling Plans for Preliminary

Computational Experiments. Technometrics 33, 161–174.

https://doi.org/10.1080/00401706.1991.10484804

Pianosi, F., Sarrazin, F., Wagener, T., 2015. A Matlab toolbox for

Global Sensitivity Analysis. Environmental Modelling & Software 70,

80–85. https://doi.org/10.1016/j.envsoft.2015.04.009



11:42 - 12:00

Heat zoning- and district heating simulation tool

Raf De Herdt, Joris Dedecker, Thomas Koch, Pedro Pattijn

Ingenium NV, Belgium

Aim and Approach

(max 200 words)

A lot of ambitious cities in Flanders are looking for a way to replace the fossil fuel heating systems for building heating to decarbonize the cities. A GIS-based simulation tool can help local governments in finding opportunities for local heat exchange and support the choice for a certain heat strategy.

Scientific Innovation and Relevance

(max 200 words)

- GIS-based tool, based on geographical open source data

- Analyzing heat demand on an urban or regional scale

- Analyzing the renovation potential on an urban or regional scale

- Analyzing potential heat sources on an urban or regional scale

- Easy routing and dimensioning of district heating grids

- Generation of environmental and financial cost

Preliminary Results and Conclusions

(max 200 words)

GIS-based tools, based on geographical open data can be useful to acquire insight in the heat flows in the city, detecting key buildings and possible locations for local heat exchange and support the choice of the local government for a heat strategy for each district to replace fossil fuels. It can allow an analysis of the potential of district heating for individual districts.

Main References

(max 200 words)

https://episcope.eu/welcome/ (2021)

 
10:30 - 12:00Session W1.4: Climate change and bioclimatic design
Location: Concert Hall - Studio 2
Session Chair: Georgios Kyriakodis, CSTB
Session Chair: Wim Plokker, Vabi
Concert Hall - Studio 2 
 
10:30 - 10:48

The impact of climate change on the reliable optimization for energy and economic refurbishment of a residential building in Italy

Amedeo Pezzi, Marco Manzan, Paolo Rosato

University of Trieste, Italy

Aim and Approach

(max 200 words)

This paper investigates the effects of data uncertainty in an optimization process applied to the refurbishment practice of a residential building focusing in particular on the effects produced by climate change. Both heating and cooling performances are considered in the optimization process. The refurbishment measures considered in this work are different levels of insulation of the opaque surfaces, the substitution of existing windows with more efficient ones and interventions on the plant system like the replacement of the generator. In order to consider also the evolution of the economic situation in which the building is supposed to work a stochastic variation of economic indexes and fuels cost is considered. Using modeFRONTIER software for the optimization and EnergyPlus and Python scripts for the numerical energy simulation, this paper searches for robust refurbishment solutions, that are the solutions that can maintain their optimality for a given range of the input parameters.

Scientific Innovation and Relevance

(max 200 words)

This paper couples the benefic effects of the optimization methods with the concept of robustness of the proposed solutions, ensuring that said solutions could maintain their optimality also in case of input data variability. Moreover, the effect of climate change on the refurbishment process is introduced as a stochastic input, calibrating the improvement interventions considering also the future environment in which the refurbished solution will work.

Preliminary Results and Conclusions

(max 200 words)

Preliminary results have been obtained through the imposition of the maximization of the Net Present Value and the minimization of the Primary Energy consumptions as optimization objectives.

The implementation of economic stochastic parameters and of the effects of climate change in the input data pool is expected to confer to the process major reliability about the future performance of the refurbished system in a broader set of different working conditions. Moreover, the climatic data variation is expected to highlight how the different external conditions could influence the importance of choosing between interventions more focused on winter or summer season and how this choice could alter the performances in the other season.

Main References

(max 200 words)

Marco Manzan, Giorgio Lupato, Amedeo Pezzi, Paolo Rosato, Alberto Clarich. Reliability-based optimization for energy refurbishment of a social housing building. Energies 2020, 13, 2310.

Giorgio Lupato, Marco Manzan, Amedeo Pezzi, The effect of climatic data on building performance optimization, BSO18 Building Simulation and Optimization, 4th IBPSA-England Conference BSO 2018, Cambridge, 11th-12th September, 2018.

Pierangioli L., Cellai G., (2016). The Impact of Climate change on energy-efficient refurbishment of social housing stock in Italy, 3rd IBPSA-England Conference BSO 2016, Newcastle, 12th-14th September.

Stephen E Belcher, Jacob N. Hacker, D.S. Powell. Constructing design weather data for future climates. Building Service Engineering Research and Technology 2005, 26.



10:48 - 11:06

Integrated design of refrigerant, heat pump and system components: Process intensification for optimized heat pump systems

Christian Vering, Sebastian Ostlender, Fabian Wuellhorst, Philipp Mehrfeld, Dirk Müller

RWTH Aachen University, Germany

Aim and Approach

(max 200 words)

In the future, heat pumps enable a sustainable building sector heat supply by using a power source that is mostly driven by renewable energies. However, high investment and operational costs currently restrain the market penetration of the technology. Conventional designs lead to oversized heat pumps to ensure security of supply. Oversizing might consequently lead to efficiency losses due to part load operation, which re-duces the overall ecologic potential of heat pumps. To fully assess the potential in the design process of heat pump systems, decisions on three levels must be considered simultaneously: Refrigerant, heat pump unit and system level components. In the context of this paper, the latter includes the heat pump, the heat-ing rod, the buffer tank and the domestic hot water tank as well as the control system. All three levels interact with each other. However, current design methods consider these levels separately. A procedure for the integrated design of the three levels does not exist for building energy systems.

Scientific Innovation and Relevance

(max 200 words)

In process engineering however, the method of process intensification offers a systematic approach for an integrated design. This method is applicable for the design of heat pump systems. In this paper, we present systematic process intensification of heat pump systems and select metrics to optimize. The refrigerant cycle of the heat pump is modelled using a performance map approach, which is obtained by stationary simulations for each combination of fluid and process flowsheet. Specifying a set of fluids and process flow-sheets, a superstructure is derived. Subsequently, a multi objective genetic algorithm solves the mixed inte-ger nonlinear optimization problem. Annual simulations ensure that the influence of the operation on the design is considered respectively. To account for varying system constraints, scenarios are specified. A sce-nario includes weather data, building parameters and geographical location.

Preliminary Results and Conclusions

(max 200 words)

The presented method enables the integrated, cost and emission optimal design of fluid, heat pump and system components simultaneously. Compared to conventional design methods, annualised costs are re-duced by 15 % and emissions by 10 % using the same fluid and process flowsheet. Concurrent, the nominal thermal power of the heat pump is reduced by up to 50 %. Furthermore, the best choice of working fluid and process flowsheet is given due to the superstructure-based approach. We solve the optimization prob-lem for different typical buildings of the German building stock. Therefore, we obtain a set of relevant refrigerants, process flowsheets and sizes of system components. This set may guide decisionmakers towards a sustainable and affordable heat supply of the German building sector. All presented results underline the po-tential of systematic process intensification to establish cost-effective and sustainable supply systems in the building sector.

Main References

(max 200 words)

Lutze, Philip, Rafiqul Gani, and John M. Woodley. "Process intensification: a perspective on process synthesis." Chemical Engineering and Processing: Process Intensification 49.6 (2010): 547-558.

Vering, Christian; Brinkmann, Katharina; Maier, Laura; Lauster, Moritz; Mueller, Dirk. (2019). Vergleich der Jahresarbeitszahlen normativ ausgelegter Wärmepumpensysteme - Teil 1. HLH. 1. 68-71.

Schilling, Johannes, Christian Horend, and André Bardow. "Integrating superstructure‐based design of molecules, processes and flowsheets." AIChE Journal: e16903.



11:06 - 11:24

Modeling the impact of Climate Change on Future Heating Demand in Different Types of Buildings in the Belgian residential building stock

Essam Elnagar1, Sébastien Doutreloup2, Vincent Lemort1

1Thermodynamics Laboratory, Aerospace and Mechanical Engineering Department, Faculty of Applied Sciences, Université de Liège, Belgium; 2Laboratory of Climatology, Department of Geography, UR SPHERES, University de Liège, Belgium

Aim and Approach

(max 200 words)

In recent years, global warming has a large impact on many aspects of the environment and human activities in buildings. Energy consumption for heating and cooling is directly affected by climate change. The residential buildings of Belgium have an average energy consumption 70% higher than the EU average. The behavior of Belgian residential building stock in terms of energy consumption is very valuable as it will help policy makers to formulate and design targeted measures for global warming aimed at improving energy efficiency and establishing current legal standards and benchmarks in the energy sector. The objective of the present study is to upscale the impact of climate change on the residential building and to evaluate its influence on the heating demand at the national level. This paper first presents the entire housing stock in Belgium which is divided in 992 cases for the reference year 2012. A weighting factor to represent their occurrence in the existing Belgian building stock is associated to each building type. The energy simulation are done for 12 case studies representing the different building types.

Scientific Innovation and Relevance

(max 200 words)

A tree structure model defining Belgian housing typology was created, characterizing Belgian residential building stock in terms of various parameters like building age, scale, level of insulation and energy vectors dedicated to domestic hot water production and space heating. The entire model is validated at national level on the basis of the gas and electricity profiles and the profiles generated are compared to available Synthetic Load Profiles (SLP). The simulation model assumes a uniform repartition of residential buildings over Belgium. The model has also been used for accounting of future climate forecasts for the period 2012 to 2100 and consideration of production and emissions systems for the space cooling. The heating and cooling degree day approach is used to assess the effect of climate change on building energy use with potential weather data by calculating new heating and cooling degree days. The multi-zone model calculation is carried out by improving the model to consider the thermal transmission and cross ventilation between different zones.

Preliminary Results and Conclusions

(max 200 words)

A dynamic building simulation model is used to focus on the future evolution of building heating energy demands. This study aims to assess the evolution of the profiles of final energy consumptions at the Belgium level with the predicted evolution of the climate until the end of the current century. 12 case studies are simulated representing 4 different building types to assess the impact of climate change on the heating demand in the different types of buildings considering the different factors of insulation and years of construction. The results show a significant decrease in the future heating demand in the upcoming years especially between the period 2050-2100.

Main References

(max 200 words)

1. An analysis on energy efficiency initiatives in the building stock of Liege, Belgium. MK Singh, S Mahapatra, J Teller - Energy policy, 2013 - Elsevier.

2. Climate change impacts on building heating and cooling energy demand in Switzerland. T Frank - Energy and buildings, 2005 - Elsevier.

3.The characteristics and the energy behaviour of the residential building stock of Cyprus in view of Directive 2002/91/EC. GP Panayiotou, SA Kalogirou, GA Florides… - Energy and …, 2010 - Elsevier.

4.Impact of climate change heating and cooling energy use in buildings in the United States. H Wang, Q Chen - Energy and Buildings, 2014 - Elsevier.



11:24 - 11:42

Climate change sensitive overheating assessment in dwellings: a case study in Belgium

Ramin Rahif1, Abdulrahman Fani1, Piotr Kosinski2, Shady Attia1

1Sustainable Building Design Lab, Dept. UEE, Faculty of Applied Sciences, Université de Liege, Belgium; 2Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, Heweliusza Street 10, 10-724 Olsztyn, Poland

Aim and Approach

(max 200 words)

Due to the current rate of global warming, overheating in buildings are expected to be more frequent and intense in future climates. High indoor temperatures affect occupants’ comfort, productivity, and health. As a result, our research is intended to investigate the vulnerability of dwellings to overheating risk in relation to the climate change. More specifically, this paper is aimed at quantifying the impact of high outdoor temperatures on building thermal conditions and long-term annual overheating risk.

By exploring a large body of the literature and standards, we decided to select the overheating assessment method suggested by (Hamdy et al., 2017). Three metrics are used namely, Indoor Overheating Degree (IOD), Ambient Warmness Degree (AWD), and Building Climate Vulnerability Factor (BCVF). The overheating risk is assessed under four climate scenarios representing historical and future scenarios. This method accounts for both severity and frequency of overheating taking into account zonal occupancy profiles and thermal comfort models. Finally, the potential of ventilative cooling is assessed in mitigation of overheating risk. The abovementioned method is applied to a lightweight single-family Passive House with total surface area of 174 m2 located in Eupen, Belgium.

Scientific Innovation and Relevance

(max 200 words)

This study applies state-of-the-art method for climate change sensitive overheating assessment in a new building in Belgium. The new buildings are more likely to become overheated due to applied measures for energy-saving purposes during the winter such as high insulation and airtightness levels. Thus, the current study assigns a lower outdoor base temperature in calculation of AWD. Also, our focus is on long-term annual overheating risk rather than short-term heatwave events or seasonal overheating phenomenon (Hamdy et al., 2017). Three fit-to-purpose metrics are introduced by modifying the calculation period of IOD, AWD, and BCVF metrics. This approach allows us to distinguish between short- and long-term overheating assessments.

Our research contributes to overheating evaluation methods in residential buildings. The research outcomes can be used to assess the cooling systems’ performance and effectiveness of adaptation measures in changing climate. Overall, this paper provides essential basis to improve indoor thermal conditions and climate change resilient design of buildings which are within the scope of IBPSA 2021 conference.

Preliminary Results and Conclusions

(max 200 words)

The results of the current study are as following: (a) distribution of annual running mean outdoor temperature under four climate scenarios, (b) ranges of annual mean, maximum, and minimum indoor operative temperature for base case and for minimum and maximum ventilation rates under four climate scenarios, (c) yearly IOD and AWD values for base case and for minimum and maximum ventilation rates under four climate scenarios, (d) climate change vulnerability assessment for base case and for minimum and maximum ventilation rates using BCVF metric, (e) evaluation of ventilative cooling potential to reduce the overheating risk under four climate scenarios.

To conclude, this research gives an insight on whether the new buildings that are in compliance to the Passive House standard are able to suppress the increase in average outdoor temperature in future climates. It also reveals the potential of ventilative cooling as a mitigation strategy and predicts to what extend its potential will decrease as global warming increases.

Main References

(max 200 words)

ASHRAE, A. (2017). Standard 55-2017. Thermal environmental conditions for human occupancy.

Butcher, K., and Craig, B. “Chartered Institution of Building Services Engineers,” Environ. Des. CIBSE Guide Eighth Ed. Ed CIBSE Guide Chart. Inst. Build. Serv. Eng. Lond., 2015.

Carlucci, S., & Pagliano, L. (2012). A review of indices for the long-term evaluation of the general thermal comfort conditions in buildings. Energy and Buildings, 53, 194-205.

Carlucci, S., Bai, L., de Dear, R., & Yang, L. (2018). Review of adaptive thermal comfort models in built environmental regulatory documents. Building and Environment, 137, 73-89.

CEN, EN 16798-1: Energy performance of buildings–ventilation for buildings–Part 1: Indoor environmental input parameters for design and assessment of energy performance of buildings addressing indoor air quality, thermal environment, lighting and acoustics. European Committee for Standardization Brussels, 2019.

Hamdy, M., Carlucci, S., Hoes, P. J., & Hensen, J. L. (2017). The impact of climate change on the overheating risk in dwellings—A Dutch case study. Building and Environment, 122, 307-323.

Khovalyg, D., Kazanci, O. B., Halvorsen, H., Gundlach, I., Bahnfleth, W. P., Toftum, J., & Olesen, B. W. (2020). Critical review of standards for indoor thermal environment and air quality. Energy and Buildings, 109819.

 
10:30 - 12:00Session W1.5: The role of occupants
Location: Concert Hall - Kamermuziekzaal
Session Chair: Fabian Ochs, University of Innsbruck
Session Chair: Valentin Gavan, ENGIE Lab CRIGEN
Concert Hall - Kamermuziekzaal 
 
10:30 - 10:48

Influence of the hydronic loop configuration on the energy performance of a CO2 heat pump for domestic hot water production in a multi-family building

Matteo Dongellini, Claudia Naldi, Gian Luca Morini

Department of Industrial Engineering, University of Bologna, Italy

Aim and Approach

(max 200 words)

Nowadays the impact of domestic hot water (DHW) production on the overall energy consumption of a building is significantly increasing. In fact, a strong effort has been made to improve the building envelope insulation properties and the efficiency of HVAC systems for space heating and cooling, while, on the contrary, a lower attention has been focused on the reduction of the energy need related to DHW preparation. Although it accounts for about the 19% of the total energy demand of European Union residential sector [1], this percentage is expected to increase up to 50% in the next years [2]. CO2 heat pumps are promising solutions to achieve significant energy savings for DHW production; furthermore, CO2 is characterized by a low GWP value, is economic and environmentally sustainable [3]. In this paper the annual energy performance of a centralized plant for DHW production in a multi-family building located in Bologna (Italy) and based on an air-to-water CO2 transcritical heat pump has been assessed by means of TRNSYS and compared with the results of a monitoring campaign performed for three months during the winter season of 2017-2018.

Scientific Innovation and Relevance

(max 200 words)

The multi-family residential building considered in this work is composed by 7 stories and 27 flats, for a total useful surface of about 3850 square meters. A particular effort has been made to determine the hot water tap profile of the whole building: the method presented in Reference [4] has been used and adapted to the selected application. A hourly draw-off profile which takes into account the contemporaneity factor of the hot water request among all the apartments has been defined for both workdays and weekends. Moreover, the dynamic model of the CO2 heat pump has been developed with the cooperation of the heat pump manufacturer, who provided the performance data of the unit and its control logic. In order to decrease the temperature of the fresh water entering the heat pump, two water storages are connected in series with the unit. This work allows to evaluate the influence of the hydronic loop configuration on the energy performance of a CO2 heat pump: dynamic simulations evidenced that the configuration initially adopted for the DHW distribution was not able to exploit the maximum energy saving potential of this kind of heat pump units.

Preliminary Results and Conclusions

(max 200 words)

The comparison between experimental and numerical results showed that the CO2 heat pump effective energy performance were much lower than that expected if the heat pump had been conducted in an optimal way. More in detail, the measured average heat pump performance factor (SPF) during the monitored period was 1.66, while, on the other hand, the unit energy performance calculated with dynamic simulations for the same interval could reach values close to 4.70. The analysis pointed out that this strong reduction of the heat pump performance was caused by the configuration of the DHW loop: with the adopted solution, thermal stratification within the storage was not obtained and the temperature of the water at the inlet of the heat pump was very high. For this reason, the unit efficiency dramatically decreases. Experimental data confirms this hypothesis: the temperature of the water stream entering the heat pump was around 40°C, almost 25 K higher than fresh water temperature introduced in the thermal storage vessel from the aqueduct. The results obtained in this work highlight how the energy performance of CO2 heat pumps is significantly influenced by the configuration of the DHW loop and especially by the layout of the thermal storages.

Main References

(max 200 words)

[1] T. Kitzberger, D. Kilian, J Cotik, T. Proll, Comprehensive analysis of the performance and intrinsic energy losses of centralized Domestic hot Water (DHW) systems in commercial (educational) buildings, Energy and Buildings 195 (2019), 126-138.

[2] A. Bertrand, A. Mastrucci, N. Schuler, R. Aggoune, F. Maréchal. Characterisation of domestic hot water end-uses for integrated urban thermal energy assessment and optimization, Applied Energy 186 (2017), 152-166.

[3] k. Visser, Transcritical CO2 refrigeration systems for building cooling and heating reduce energy and cooling water consumption, emissions and the legionella danger, Proceedings of the 8th International Conference on Advances in Applied Science and Environmental Engineering (ASEE 2018), 3-4 February 2018, Kuala Lumpur, Malaysia.

[4] K. Ahmed, P. Pylsy, J. Kurnitski, Hourly Consumption profiles of domestic hot water for different occupant groups in dwellings, Solar Energy 137 (2016), 516-530.



10:48 - 11:06

Methods for determining occupant behavioural models for energy-efficient retrofitting of 20th-century buildings

Antonella Mastrorilli1, Roberta Zarcone2, Chenafi Sabrina1, Colonneau Téva1

1Laboratoire LACTH, Ecole Nationale Supérieure d’Architecture et de Paysage de Lille, 2 Rue Verte, 59650 Villeneuve-d'Ascq, France; 2Laboratoire GSA, Ecole Nationale Supérieure d’Architecture Paris-Malaquais, 14 rue Bonaparte, 75006 Paris

Aim and Approach

(max 200 words)

A study carried out within the project "Rethinking innovation. Know and manage the legacies of experiment and innovative social housing from the decade 1968-78” funded by the French Ministry of Cultural, is presented in this paper. The objective of this research is to highlight the influence of the variable occupancy in an energy renovation scenario.

We present the methodology developed for the construction of a "detailed" inhabitant profile on a case study of the social housing “Residence Salamandre” in Villeneuve d'Ascq.

By using an interoperable work, we produced a digital model informed by BIM methods, combining the sharing of information tasks of existing construction and site conditions.

From the typo-morphological analysis of the housing modules, a phase of data collection on the lifestyles of different occupants of the residence was developed. The balance sheet of energy consumed by year (provide by inhabitants) and anonymous surveys made it possible to link the aspect of daily consumption to the question of lifestyles.

In this paper, we present the impact of internal contributions on energy performance by comparing the results with those resulting from the application of usage scenarios in accordance with the French RT2012 standard.

Scientific Innovation and Relevance

(max 200 words)

Today, the influence of occupants’ behaviour is oversimplified during the analysis phases prior to energy renovation operations.

Amongst other variables, the lifestyles of the occupants remains one of the most difficult to control. However, it seems to play a decisive role because it represents one of the main factors of discrepancy between the phases of energy renovation and the actual functioning of a building.

Assessing energy needs and performance of existing buildings therefore, requires calculation tools able to produce results that are closest to reality. However, the different energy simulation softwares show many disparities which often leads to different results. In addition, the application of thermal regulations requires the use of referenced conventional calculation methods (DPE, TH BCE Method), certifying a level of energy performance to reach, by combining the analysis of "real" data with those of predetermined data, from hypothetical use scenarios.

This research attempted to develop dynamic energy simulation methods, offering the most realistic representation of energy needs in use conditions. We have defined a "fine" analysis methodology which allowed to take into account the variable of occupancy in housing. This will make us quantify its impact on energy needs and prefigure the most appropriate energy intervention.

Preliminary Results and Conclusions

(max 200 words)

According to the simulations carried out through numerical modelling and the characterisation of a "detailed" user profile - for a family of three people - the first results obtained have demonstrated the impact of Inhabitants users in the calculation of consumption needs.

In fact, in the case of the “detailed” user profile, the internal contributions cover a total of 40% of the home's heating needs, i.e. 10% more than the results obtained considering the conventional profile from the French standard RT2012.

The results then highlighted a striking observation: Through dynamic energy building simulation, the occupancy variable in “detailed” user profile shows more efficient alternative than the intervention in external over-insulation of the Salamandre residence, with a strong aesthetic and constructive impact as a whole. Resorting to a "fine" analysis on a case-by-case basis - provide by actual measurements of occupancy variables in the dwelling - might then be more appropriate, in order to preserve the original aesthic and material qualities of building heritage objects.

Therefore, the conceptual and technical results obtained in this research aim to generalize this analysis methodology prior to each energy renovation project for existing buildings.

Main References

(max 200 words)

Fabi V, Andersen RV, Corgnati SP, Olesen BW. A methodology for modelling energy-related human behaviour: application to window opening behaviour in residential buildings. Build Simul 2013 6:415

Andersen RV, Toftum J, Andersen KK, Olesen BW (2009), “Survey of occupant behaviour and control of indoor environment”, Danish dwellings. Energy and Buildings, 41: 11–16

Andersen RV (2012), “The influence of occupants’ behaviour on energy consumption investigated in 290 identical dwellings and in 35 apartments”, Proceedings of Healthy Buildings 2012, Brisbane, Australia.

Brundrett GW (1997), “Ventilation: A behavioural approach”, International Journal of Energy Research, 1: 289–298. Emery AF, Kippenhan CJ (2006), “A long term of residential home heating consumption and the effect of occupant behavior on homes in the Pacific Northwest constructed according to improved thermal standards”, Energy, 31: 677-693.

Geslin F., Le bâti ancien appelle des solutions non standardisées, Les cahiers techniques du bâtiment, (https://www.cahiers-techniques-batiment. fr/article/le-bati-ancien-appelle-des-solutions-non standardisees.32324, consulté le 28/03/2017).

Nicol JF, Humphreys MA (2004), “A stochastic approach to thermal comfort-occupant behaviour and energy use in buildings”, ASHRAE Transactions, 110(2): 554–68.



11:06 - 11:24

Human in the Loop: perceived based control as the key to enhance buildings’ performance

Davide Calì, Christian Ankerstjerne Thilker, Sebastian Arcos Specht, Jaume Palmer Real, Henrik Madsen, Bjarne W. Olesen

DTU, Denmark

Aim and Approach

(max 200 words)

The performance gap of existing and new buildings [1], both in terms of energy and occupants’ comfort, jeopardizes the effort to reach deep decarbonization target. One of the main issues causing high CO2 emissions of buildings is related to VOLATILITY. Buildings are mostly planned and controlled based on assumptions and fixed schedules which might were valid in the Sixties. However, our society evolved: For example, residential buildings where family lives are often empty during the day while both parents go to work and children stay until afternoon at schools; in parallel, work-from-home became reality, also several times a week. Moreover, not only the demand for comfort is volatile: to minimize buildings’ impact on climate change, we have to maximize the use of renewable energy sources. As a consequence, the production of energy is non-projectable. Matching the volatile usage of buildings with intermittent energy production can help both enhancing personal comfort and reducing CO2 emissions caused by the existing building stock. In this work, we propose a Human-in-the-Loop approach, where occupants are traced within a building, and, when they desire it, can provide feedback about their perceived comfort in specific rooms: this feedback is then used to control the building.

Scientific Innovation and Relevance

(max 200 words)

The provision of flexibility services to the energy grids became more popular in the last decade. However, too often flexibility projects have a strong focus on the quality of the services provided to the grid, and do not actively consider real occupants needs. Eventually, flexibility services are connected to a deficit of indoor comfort (e.g. accepting lower indoor temperature or lower air change per hour). Through the use of our tracing and feedback app “FEEDME” and a network of IoT sensors connected to our vendor-neutral monitoring platform CLIMIFY [2], we gather information regarding the number of occupants within a room, their live feedback on the indoor climate, and their past preferences at given indoor conditions. This information can be used to:

1. Simplify the way buildings are controlled: instead of asking the occupants to choose set points, we ask how she/he feels, and control the building accordingly

2. Take into account the diversity of occupants’ needs, and also the way those needs change during the day in the control of buildings - Mediate among different needs in a democratic way;

3. Optimize energy use, CO2 emissions and indoor climate in buildings through model predictive control and AI.

Preliminary Results and Conclusions

(max 200 words)

FEEDME and CLIMIFY are currently being tested in a school with 13 classrooms, located in Denmark (a second demonstration office building is under arrangement). In the school, we gathered the feedback of occupants on their perceived thermal comfort (using a 5-steps scale) for a period of 6 weeks. In a first 3-week period, the set-point of smart thermostats was for all classrooms set to 22°C: 51% of the occupants were fully satisfied with the indoor climate, while over 10% were completely dissatisfied. In the second 3-week period, the set points of each classroom were manually adjusted accordingly to the received feedback of the previous 3 weeks. As a result, over 63% of occupants were fully satisfied, only 6% was fully unsatisfied [5]. In this first experiment, we only adjusted the set-point once, and accordingly to the location were the feedback was given only. A real time optimization, considering the exact occupants in each classroom and adjusting also other set-points, such as ventilation and blinds, could further enhance occupants experience in buildings. FEEDME keeps the occupants in the middle of the control loop but minimizes human errors. Moreover, the indoor climate enhancement is reflected into higher productivity [4, 5].

Main References

(max 200 words)

[1] D Calì, T Osterhage, R Streblow, D Müller, Energy performance gap in refurbished German dwellings: Lesson learned from a field test - Energy and buildings, 127 (2016), 1146-1158. https://doi.org/10.1016/j.enbuild.2016.05.020

[2] Calì, D., Kindler, E., Ebrahimy, R., Bacher, P., Hu, K. S., Østrup, M. L., Bachalarz, M., & Madsen, H. (2019). climify.org: an online solution for easy control and monitoring of the indoor environment. E3S Web of Conferences, 111. https://doi.org/10.1051/e3sconf/201911105006

[3] D. Calì, Results of data analysis and optimization algorithms - Technical Report, DTU, 2020.

[4] P. Wargocki, J.A. Porras-Salazar, S. Contreras-Espinoza, The relationship between classroom temperature and children’s performance in school, Build. Environ. 157 (2019) 197–204. https://doi:10.1016/j.buildenv.2019.04.046

[5] P. Wargocki, J.A. Porras-Salazar, S. Contreras-Espinoza, W. Bahnfleth, The relationships between classroom air quality and children’s performance in school, Build. Environ. 173 (2020). https://doi:10.1016/j.buildenv.2020.106749



11:24 - 11:42

A simulation workflow for exposure characterisation of daylit spaces based on occupant gaze orientation

Mandana Sarey Khanie1, Mikkel Kofod Pedersen1, Trine Illum1, Rasmus Nielsen1, Thorbjøn Asmussen2

1Technical University of Denamrk, Denmark; 2VELUX A/S, Hoersholm, Denmark

Aim and Approach

(max 200 words)

This paper represents a simulation workflow for characterization of spectral exposure depending on occupants’ position and gaze behavior in buildings. The project uses existing gaze movement database as well as occupant-tracking data obtained in a pilot study for its development. The existing database has been obtained at a daylight lab at Freiburg, Germany, in a user-assessment study where eye-tracking systems were used to record visual responses to the luminous environment [1]. The pilot study was done over a period of 2 months where occupants’ orientations were tracked using an image-based sensors recoding dwells and movements of occupant. The dwell and track data from the pilot study were used to define exposure ranges to spectral effectiveness of the space. Using the two databases , a Grasshopper3D tool was developed to demonstrate gaze behavior[1], [2], exposure to illumination levels, and the exposure to spectral lighting, thus allows for exposure characterization of the space at the eye level at each given position. The latter was processed using Lark Spectral Lighting tool [3] to account for photopic, Rea[4] and Lucas [5]circadian illuminance. Using the tool, a simulation study was done and the results as well as the work flow are presented here.

Scientific Innovation and Relevance

(max 200 words)

Despite different existing wavelength-dependent models to predict spectral-effectiveness of light[6], [7], these methods can only predict the health potentials in a space with assumption of static building occupants on fixed pre-defined points[8]. With great benefits on our well-being [9], [10], an exposure characterization of space for daylight, based on dynamic occupant behavior is a step forward. This step allows for better understanding occupant well-being indoors based on actual occupant’s position and orientation. The dynamic human behavior to light exposure has been addressed in fewer studies where photometric measurements and eye-tracking methods were coupled for observations of gaze or eye responses to light [1], [11]. Building up on these exiting methodologies, here the occupant light-driven behavior is used to predict the exposure to spectral lighting and illumination levels in space. In addition, data gathered by the sensors are processed to show the actual exposure levels in real time. The developed tool and processing method can be used in design phases to introduce interventions, e.g. change of interior layout, for optimal lighting solutions.

Preliminary Results and Conclusions

(max 200 words)

The simulation study provided a clear demonstration of visual patterns and exposure patterns at different points in space based on the dynamic occupant behavior. The health potential of the selected dominant gaze orientation was evaluated at each position. From the Lark tool [6], the values had to be converted as the selected threshold values used the units Circadian Stimulus (CS) and Equivalent Melanopic Lux (EML). The threshold value CS explained the optimal stimulus throughout the working day, where specific values are given for each hour, while the threshold value EML gave a fixed value over all hours. While most positions in the models showed satisfactory during summer time and under sunny conditions, only fewer positions would reach the thresholds under overcasts skies. Hence, optimized use of such areas in certain climatic regions proves to be essential. Moreover, as in north façade and lack of visual discomfort allows for orienting towards windows, higher health potentials can be achieved. It can therefore be concluded that the orientation in space is crucial for the vertical illuminance measured at the eye, but it is still important that the visual comfort is maintained.

Main References

(max 200 words)

1. Sarey Khanie, M., et.al. Gaze and discomfort glare, Part 1: Development of a gaze-driven photometry. Light. Res. Technol. (2016)

2.Sarey Khanie, M. et al. A Gaze Visualizer tool for Grasshopper3d. in SimBuild – USA, (2018)

3. Inanici, M., et.al. Spectral daylighting simulations, Department of Architecture, Seattle, USA

4. Rea, M. The lumen seen in a new light, Light. Res. Technol. 47, (2015)

5.Lucas, R. et al. Measuring and using light in the melanopsin age. Trends in Neurosciences (2014).

6.Amundadottir,M. et.al. Unified framework to evaluate non-visual spectral effectiveness of light for human health. Light. Res. Technol. 49, (2017)

7. Rea, M., et.al. A new approach to understanding the impact of circadian disruption on human health. J Circadian Rhythm. 6, (2008)

8.Amundadottir, M. et.al. A human-centric approach to assess daylight in buildings for non-visual health potential, visual interest and gaze behavior. Build. Environ. 113, (2017)

9. Lockley, S. Circadian Rhythms: Influence of Light in Humans. Encycl. Neurosci. 2, (2009)

10.Birchler-Pedross, A. et al. Subjective Well-Being Is Modulated by Circadian Phase, Sleep Pressure, Age, and Gender. J. Biol. Rhythms 24, (2009)

11.Lin, Y. et al. Eye movement and pupil size constriction under discomfort glare. Invest. Ophthalmol. Vis. Sci. 56, (2015)



11:42 - 12:00

Quantifying household specific self-consumption of photovoltaic-based power generation in energy efficient buildings – a comprehensive parametric study to increase the reliability of energy consulting

André Müller1,2, Johannes Koert2, Patrick Wörner2

1Institute for Housing and Environment, Germany; 2Institute of Concrete and Masonry Structures, Technische Universität Darmstadt, Germany

Aim and Approach

(max 200 words)

The energy consumption from private households is responsible for a substantial share of the total greenhouse gas emissions in Germany. For this reason, German legislation promotes the climate-neutral operation of buildings until 2050. Consequently, building related power generation from renewable energies can be considered in the calculation of energy performance according to the German Energy Saving Ordinance (EnEV). However, the EnEV calculation rules allow neither for a proper estimation of the amount of renewable energy generated locally from PV nor for the estimation of private electricity consumption. Thus, the assessments of PV systems to be installed on buildings lack reliability and highly depend on the modelling skills of the energy consultant. To overcome this barrier for the implementation of building-related PV an easy applicable matrix of energy generation and private consumption for different locations as well as types of buildings and households is developed. This is achieved by feeding IDA ICE building simulation models with profiles generated by the user behaviour model ‘PeakTime’. Typical user behaviour of certain household types is translated to annual power consumption profiles, added to the load profiles of building archetypes and compared to the electrical power generation profiles from a PV system.

Scientific Innovation and Relevance

(max 200 words)

A variety of studies already exist on the self-consumption of power production from building related PV systems. However, most of these narrowed research down to a single or respectively a few real or typical households’ electricity consumption. Thus, the results allow for a plausible estimation of self-consumption, but not for a detailed prognosis and quantification as the source of reliable energy consulting. The basis of the presented investigation on household-type specific PV self-consumption is a recently developed stochastic user behaviour model, which allows the generation of load profiles for power consumption of various household configurations. Thereby, household specific circumstances, e.g. the co-use of electrical appliances by two or more household members, and their effect on households’ load profiles are reflected. The relevance arises from the fact that, besides calculated standard load profiles for household types, a distribution of self-consumption from PV systems emerges. To allow for a proper comparison of available technologies and energy performance levels, the household load profiles are processed in a parametric study within the building simulation software IDA ICE. The results of these simulations are categorized and summarized to achieve applicability in the context of energy consulting and allow for more profound decisions of building owners.

Preliminary Results and Conclusions

(max 200 words)

The preliminary results illustrate the fact, that power consumption of household types differ dependent on the status of employment household members and the presence of kids, respectively. At the same time, the amount of self-consumption from PV generated power is highly correlated to the user behaviours underlying the household types. While energy performance calculations according to German EnEV calculation rules cannot reflect these variations, the performed parametric study gives reliable values for self-consumption in general as well as ratios of solar coverage of the use cases heating and cooling, hot water demand as well as other electrical appliances of a household. Thereby, the preliminary results build on a reduced number of available household types and represent an intermediate step on the way of making available realistic user behaviour data for energy performance calculations as well as dynamic building simulations.

Main References

(max 200 words)

Yan, Da ; Hong, Tianzhen; Dong, Bing; Mahdavid, Ardeshir; D’Oca, Simona; Gaetanie, Isabella; Fenga, Xiaohang (2017): IEA EBC Annex 66: Definition and simulation of occupant behavior in buildings. Energy and Buildings, Volume 156, Pages 258-270.

Wörner, Patrick (in Press): Einfluss des Nutzerverhaltens auf den Stromverbrauch in Wohngebäuden ‐ Entwicklung eines komplexen Simulationsmodells für energetische Analysen. Dissertation. Institute of Concrete and Masonry Structures, Technische Universität Darmstadt. Graubner, Carl-Alexander (Ed.)

Loga, Tobias; Frank, Milena (2016): Photovoltaic power generation to cover domestic power demand in Passive House: A parameter study. 20th International Passive House Conference 2016: 22th – 23th April 2016, Darmstadt: Proceedings / Passive House Institute. Feist, Wolfgang (Ed.)

https://www.iwu.de/fileadmin/user_upload/dateien/energie/neh_ph/2016_passivhaustagung_LogaFrank_PVEigendeckungImPassivhaus.pdf (German version; English version is available to the author as print version only; last access: 31.07.2020)

Gaetani, Isabella; Hoes, Pieter-Jan; Hensen, Jan L.M. (2018): Estimating the influence of occupant behavior on building heating and cooling energy in one simulation run. Applied Energy, Volume 223, Pages 159-171.

BMUB (2016): Climate Action Plan 2050 – Principles and goals of the German government’s climate policy. Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (Ed.).

https://www.bmu.de/en/publication/climate-action-plan-2050/ (Last access: 31.07.2020)

 
10:30 - 12:00Session W1.6: Improving indoor environmental quality
Location: Concert Hall - Concertzaal
Session Chair: Hilde Breesch, KU Leuven
Session Chair: Dimitrov Bolashikov, Daikin Europe NV
Concert Hall - Concertzaal 
 
10:30 - 10:48

Computational assessment of occupant-centric radiant cooling solutions

Helene Teufl, Ardeshir Mahdavi

Department of Building Physics and Building Ecology, TU Wien, Vienna, Austria

Aim and Approach

(max 200 words)

The aim of this contribution is to computationally model and evaluate a number of previously proposed alternative radiant cooling designs [1]. The development of these solutions is guided by three main concepts. The first concept aims at positioning cooling elements in close proximity to occupants. This approach is suggested to enhance both energy efficiency and personal control. The second concept concerns the surface temperature of the radiant element. In comparison to classical radiant cooling solutions, the alternative strategies are meant to allow for and accommodate surface condensation via integrated drainage elements. Thus, lower panel surface temperatures are possible. The third concept aims at incorporating an appropriately selected vegetation layer into the designs [1, 2]. Such a layer could contribute to the appearance of the radiant panels. Moreover, placed below the vertical radiant panel, the container for the layer's substrate can act as the collector of condensed water. The paper entails a detailed computational examination of the effectiveness of the proposed solutions.

Scientific Innovation and Relevance

(max 200 words)

Buildings' increasing cooling energy use has been attributed to phenomena such as global warming and urban heat islands [3]. This underlines the need for innovative cooling solutions. In this context, radiant cooling technologies have been promoted because they have the potential to improve the energy efficiency as well as occupants' thermal comfort [4-7]. Nonetheless, some important aspects must be considered when designing and implementing radiant cooling systems (e.g., buildings' climatic context, position of the radiant elements relative to occupants, water vapor condensation risk). The previously mentioned alternative radiant cooling solutions are intended to address these aspects [1]. The contribution highlights the potential of these solutions in view of energy efficiency and thermal comfort.

Preliminary Results and Conclusions

(max 200 words)

The paper presents the result of a virtual examination of prototype designs of occupant-centric radiant cooling systems in an office setting. A software solution is developed to probe multiple design variations including panels positioned on one or two sides of typical workstations. The effectiveness of the solutions is explored for different climatic regions (from hot dry to hot humid) and multiple surface temperature regimes (involving both temperatures above and below the dew-point temperature) are considered. The outcome of the case study shows that occupant-centric radiant cooling can improve both energy efficiency and users' thermal comfort. Moreover, limitations of the proposed configurations – particularly in extremely hot and humid conditions – are illustrated, and potential complementary measures (i.e., additional convective cooling via task elements) are examined. The developed software solution can offer a preliminary virtual assessment of a variety of technical solutions in a variety of climatic boundary conditions.

Main References

(max 200 words)

1. Mahdavi, A., Teufl, H., 2020. Occupant-centric radiant cooling solutions. Requirements, designs, assessment. In PLEA 2020 (Ed.): Proceedings of the PLEA 2020 Conference – to appear.

2. Gau, U., 2005. Eine mobile Kühlwand für Büroräume. Master Thesis: TU Wien.

3. IEA, 2018. The Future of Cooling - Opportunities for energy-efficient air conditioning. https://www.iea.org/reports/the-future-of-cooling

4. Rhee, K.N., Kim, K.W., 2015. A 50 year review of basic and applied research in radiant heating and cooling systems for the built environment. Building and Environment 91, pp. 166–190. DOI: 10.1016/j.buildenv.2015.03.040.

5. Rhee, K.N., Olesen, B.W., Kim, K.W., 2017. Ten questions about radiant heating and cooling systems. Building and Environment 112, pp. 367–381. DOI: 10.1016/j.buildenv.2016.11.030.

6. Tian, Z., Love, J.A., 2009. Energy performance optimization of radiant slab cooling using building simulation and field measurements. Energy and Buildings 41 (3), pp. 320–330. DOI: 10.1016/j.enbuild.2008.10.002.

7. Memon, R.A., Chirarattananon, S., Vangtook, P., 2008. Thermal comfort assessment and application of radiant cooling: A case study. Building and Environment 43 (7), pp. 1185–1196. DOI: 10.1016/j.buildenv.2006.04.025.



10:48 - 11:06

Occupant-centric control of transparent dynamic façades through an integrated co-simulation framework

Luigi Giovannini, Manuela Baracani, Fabio Favoino, Valentina Serra

Polytechnic University of Turin, Italy

Aim and Approach

(max 200 words)

The use of adaptive transparent envelope technologies (adaptive glazings, dynamic shading devices, etc..) in buildings could yield significant performance improvements compared to static solutions, due to their ability of modulating the incoming solar radiation according to external inputs. As a consequence, these components are difficult to operate, as their behaviour simultaneously affects different physical domains, interdependent and often conflicting. Current research trends have mainly focused on controlling these technologies to minimise building energy use, while comfort aspects (thermal and visual comfort) related to their operation are generally overlooked. Nevertheless, understanding the relationship between different performance requirements in operating such dynamic systems is of outmost importance.

In this framework, this paper presents a simulation framework to evaluate the performance of adaptive transparent façades in a comprehensive way, and this is demonstrated by evaluating the performance of different mono-objective control strategies, aimed at the optimisation of either energy or comfort aspects. This is done for an office case study located in Rome and equipped with an active adaptive façade technology modulating the entering solar radiation. This enabled investigating the strengths and drawbacks of the control strategies considered, as well as their impact over physical domains these were not conceived to optimise.

Scientific Innovation and Relevance

(max 200 words)

Current Building Performance Simulation tools have limited capability in evaluating the performance of transparent adaptive technologies [1], including the influence of the control strategy, due to their inability to: (a) flexibly vary the thermo-optical properties of the materials; (b) evaluate in an integrated way the mutual effect of an adaptive envelope technology in different physical domains. As a result, most of the studies evaluating the performance of adaptive envelope components focus only on their effect on energy related aspects, visual or thermal comfort aspects, not taking into account the mutual influence between these domains. This paper presents an integrated simulation framework enabling the evaluation of the performance of active adaptive envelope technologies according to energy, thermal and daylight related aspects in a coupled way. This was done by managing together BPS tools aimed at evaluating the different aspects influenced by the adaptive component behaviour. Specifically, the use of Rhinoceros parametric plugin Grasshopper and its add-on Ladybug/Honeybee allowed different BPS tools to be managed through the same interface. EnergyPlus was used for the thermal and energy analysis while DAYSIM and Radiance were used for the daylight analysis. Finally, the data integration between these tools was achieved through purposely built scripts.

Preliminary Results and Conclusions

(max 200 words)

The results obtained for the office case study considered show that the control strategies analysed, when aimed at optimising a single objective (i.e. energy performance, visual or thermal comfort, etc..), have, at different extents, drawbacks on the other domains they influence. To prevent or reduce these drawbacks, the control strategies should be devised as most suitable trade-off between energy and comfort related aspects. Moreover, the specific features of the space considered, as well as the climate of the site, show to have a significant influence on the effectiveness of a control strategy. Based on the results obtained, in order to successfully meet the desired goals, a specific control strategy should be purposely conceived or optimised for each specific space, taking into account its characteristics and the local climate as well. The integrated simulation approach proposed in the present work can play a key role in the conception and/or optimisation of such control strategies: its ability to overcome the main gaps in the currently available simulation strategies allows in fact a simultaneous and accurate evaluation of the effects of the behaviour of an active adaptive envelope component on energy, visual comfort and thermal comfort related aspects.

Main References

(max 200 words)

[1] R.C.G.M. Loonen, F. Favoino, J. Hensen, M. Overend. Review of current status, requirements and opportunities for building performance simulation of adaptive facades, Journal of Building Performance Simulation 10(2) (2017) 205-223.

[2] L. Giovannini, F. Favoino, A. Pellegrino, V.R.M. Lo Verso, V. Serra, M. Zinzi. Thermochromic glazing performance: From component experimental characterisation to whole building performance evaluation. Applied Energy 251 (2019) 11335.

[3] L. Giovannini, F. Favoino, V.R.M. Lo Verso, A. Pellegrino, V. Serra. A Simplified Approach for the Annual and Spatial Evaluation of the Comfort Classes of Daylight Glare Using Vertical Illuminances. Buildings 8 (2018), 171.

[4] E. Arens, T. Hoyt, X. Zhou, L. Huang, H. Zhang, S. Schiavon. Modeling thecomfort effects of short-wave solar radiation indoors. Building and Environment 88 (2015), 3-9.

[5] F. Favoino, F. Fiorito, A. Cannavale, G. Ranzi, M. Overend. Optimal control and performance of photovoltachromic switchable glazing for building integration in temperate climates. Applied Energy 178 (2016), 943-961.

[6] J.M. Dussault, L. Gosselin. Office buildings with electrochromic windows: A sensitivity analysis of design parameters on energy performance, and thermal and visual comfort. Energy and Buildings, 153 (2017), 50-62.



11:06 - 11:24

Optimization workflow for the design of efficient shading control strategies

Abel Sepúlveda, Francesco De Luca, Jarek Kurnitski

Tallinn University of Technology, Estonia

Aim and Approach

(max 200 words)

The main aim of this investigation is to study optimal shading strategies to improve the indoor visual comfort and energy performance at educational buildings in Estonia.

The goals are the following:

1. Optimization of control algorithms for internal roller fabric systems to achieve a suitable daylight provision and glare performance.

2. To prove the viability of these different shading algorithms to contribute achieving the energy consumption of nearly energy zero buildings (nZEB) according to the Estonian regulation [1, 2] and minimum requirements in terms of daylight provision and glare protection defined by the novel European standard EN 17037:2018 [3].

We used a simulation-based methodology and single zone approach (room level) [4]. The software used are Radiance and EnergyPlus for daylight and energy calculations, respectively. The cases study consists in three existing auditoriums with different orientations (east, south and west) located in Tallinn University of Technology campus. We considered interior roller fabrics as main shading device. Four different complex fenestration systems are analyzed and shading controls based on vertical illuminance, direct normal irradiance and daylight glare probability (DGP) are tested.

Scientific Innovation and Relevance

(max 200 words)

Visual comfort has high impact on students’ academic performance and health. Estonian energy consumption requirements aim to reach the nearly Energy Zero Building (nZEB) category for new and renovated buildings. In addition, the fulfillment of the actual Estonian daylight requirements based on daylight factor have been proved insufficient to ensure a realistic daylight provision in residential, office and educational buildings [5]. There is a lack of consideration of daylight glare phenomenon during early stages and refurbishment plans in Estonia despite of the low sun altitude [6, 7]. Furthermore, the fulfillment of requirements in terms of daylight provision and glare protection defined by the European standard EN 17037:2018 in combination with nZEB energy requirements defined by the Estonian regulations must be studied.

Preliminary Results and Conclusions

(max 200 words)

It is possible to achieve suitable trade-off between daylight provision, glare protection and energy performance in educational buildings in Estonia. This achievement can be reached combining interior roller fabric and shading control strategies based on variables such as vertical illuminance at eye level, direct normal solar radiation and DGP are crucial to achieve an adequate overall performance. A suitable choice of the fabric and shading control algorithm thresholds helps to optimize the overall performance depending on the room orientation, surrounding buildings and weather conditions. Moreover, the use of the interior roller fabric is key to improve glare protection without increasing lighting consumption. This study would help architects and practitioners to choose adequate CFSs and their control at both, in early stages and refurbishment plans of educational buildings in Estonia.

Main References

(max 200 words)

[1] Estonian Government, Minimum requirements for energy performance. Annex 68, RT I, 24.01.2014, 3, (2012). https://www.riigiteataja.ee/en/eli/520102014001.

[2] Estonian Government, Ordinance N° 58. Methodology for calculating the energy performance of buildings. RTI,09.06.2015, 21, (2015).

[3] European comission, BS EN 17037:2018: Daylight in buildings, (2018). https://www.en-standard.eu/bs-en-17037-2018-daylight-in-buildings/.

[4] B. Bueno, A. Sepúlveda, A Specific Building Simulation Tool for the Design and Evaluation of Innovative Fenestration Systems and their Control, in: Nternational Build. Perform. Simul. Assoc. -IBPSA- Build. Simul. 2019. 16th Conf. IBPSA. Proc. Rome, Italy, 2-4 Sept. 2019, 2019. http://publica.fraunhofer.de/dokumente/N-565205.html.

[5] F. De Luca, M. Kiil, R. Simson, J. Kurnitski, R. Murula, Evaluating Daylight Factor Standard through Climate Based Daylight Simulations and Overheating Regulations in Estonia, in: Proc. Build. Simul. 2019 16th Conf. Int. Build. Perform. Simul. Assoc., 2019.

[6] Sepúlveda, A., De Luca, F., Thalfeldt, M., & Kurnitski, J. (2020). Analyzing the fulfillment of daylight and overheating requirements in residential and office buildings in Estonia. Building and Environment, 107036.

[7] F. De Luca, T. Dogan, J. Kurnitski, Methodology for determining fenestration ranges for daylight andenergy efficiency in Estonia, in: Simul. Ser., 2018. https://doi.org/10.22360/simaud.2018.simaud.007.



11:24 - 11:42

Tool Development for Automatic Simulation of central and decentral Heat Supply Scenarios and Application to a district in the City of Mainz, Germany (SimStadt 2.0 project)

Verena Weiler1, Eric Duminil1, Bodo Balbach2, Bastian Schröter1

1University of Applied Sciences Stuttgart, Germany; 2Mainzer Stadtwerke AG

Aim and Approach

(max 200 words)

Often enough, when new constructions or changes in existing built-up areas are planned, energetic assessments such as the choice among heat supply options, are done at a late stage in the process, with key decisions on the area already made. Our tool, called SimStadt, enables local decision makers to perform an early-stage analysis of possible planning scenarios, with limited data requirements on the technical backgrounds and exact design of potential future scenarios.

SimStadt is a scientific workflow management platform, which can be coupled to a number of external tools and libraries. The existing functionalities have been described in various publications ([1]–[4]) and shall not be the focus here. The new developments in the (ongoing) SimStadt 2.0 project are the connection of heat demand calculations to heat supply models. They are modelled in INSEL (www.insel.eu), with the district heating network dimensioned in more detail in STANET (www.stafu.de/en). Additionally, an energy components library contains relevant parameters for various heat supply models. The new development was tested with a district of 65 buildings in Mainz, Germany, where options for a central network system were compared against a decentral air-water heat pump system along technical and economic indicators.

Scientific Innovation and Relevance

(max 200 words)

Most urban building energy simulation tools (UBEM) need a large amount of input data and/or proficient users ([5], [6]). One innovation in the SimStadt 2.0 project and tool development lies in the fact that the simulation environment can be used by non-experts while maintaining sufficient results accuracy for strategic decision-making and comparing various options in a scenario-based approach. This semi-automatic process is facilitated by the architectural design of the SimStadt platform: a CityGML model used as key input contains most of the required information on building geometry; second, a pre-defined set of heating system configurations with underlying, INSEL-based simulation models as well as a library of component specifications from the most important manufacturers enables the user to simply choose one or more heat supply options.

Simulation results are given as tables containing important technical and economic parameters such as total investment and operating cost and GHG emissions of a given scenario, and can be visualized via 3D maps. Thus, multiple scenarios can be easily compared against each other.

Preliminary Results and Conclusions

(max 200 words)

Our approach was validated by comparing the modelling results for CHP plus centralized heating network with measured data from 2017. While actual data give a total annual heat demand of 2,005MWh, our model gives 2,144MWh, i.e. a deviation of 7%, with the simulation mainly over-estimating space heating demand for office buildings. This can partly be attributed to refurbishments that are not yet accounted for in the CityGML building data that serves as input to the simulation. Comparing the values on the supply side, measured data give 2,924MWh, which we underestimate by only 4%. When looking at the monthly comparison, differences are higher especially in March and November, when a typical heating season in Germany starts or ends (-34% and +65%, respectively). Comparing hourly values, the mean bias error is less than 10%.

Results from the model that applies decentral heat pumps in all buildings cannot be validated with measured data, since it is theoretical. However, the model was validated by comparing it to another heat pump model that itself had already been validated with measured data from a different project.

Future analysis will be aimed at identifying the reasons for the differences between measurement and simulation and consequently reducing them.

Main References

(max 200 words)

[1] R. Nouvel et al., “SIMSTADT , A NEW WORKFLOW-DRIVEN URBAN ENERGY SIMULATION PLATFORM FOR CITYGML CITY MODELS,” in CISBAT 2015, 2015, pp. 889–894.

[2] U. Eicker, D. Monien, É. Duminil, and R. Nouvel, “Energy performance assessment in urban planning competitions,” Appl. Energy, vol. 155, pp. 323–333, 2015.

[3] M. Zirak, V. Weiler, M. Hein, and U. Eicker, “Urban models enrichment for energy applications: Challenges in energy simulation using different data sources for building age information,” Energy, vol. 190, p. 116292, 2019.

[4] V. Weiler and U. Eicker, “Individual Domestic Hot Water Profiles for Building Simulation at Urban Scale,” in IBPSA Building Simulation Conference, 2019.

[5] J. Allegrini, K. Orehounig, G. Mavromatidis, F. Ruesch, V. Dorer, and R. Evins, “A review of modelling approaches and tools for the simulation of district-scale energy systems,” Renew. Sustain. Energy Rev., vol. 52, pp. 1391–1404, 2015.

[6] W. Li, Y. Zhou, K. Cetin, J. Eom, Y. Wang, and G. Chen, “Modeling urban building energy use: A review of modeling approaches and procedures,” Energy, vol. 141, pp. 2445–2457, 2017.

 
10:30 - 12:00Session W1.7 (Online Track): Ensuring high quality building simulations
Location: Virtual Meeting Room 1
Session Chair: Clarice Bleil de Souza, Cardiff University
Virtual Meeting Room 1 
 
10:30 - 10:48

Design optioneering for the definition of technological solution of envelope using BIM

Frida Bazzocchi1, Neri Banti1, Carlo Biagini2, Cecilia Ciacci1, Vincenzo Di Naso1

1University of Florence, DICEA (Department of Civil and Environmental Engineering ), Italy; 2University of Florence, DiDA (Department of Architecture), Italy

Aim and Approach

(max 200 words)

The construction sector has recently undergone an evolution both in terms of performance requirements for buildings and in relation to the management techniques of design processes to make them easier to satisfy. This is the case of BIM Information Modelling (BIM), able to ensure digital and multidisciplinary design management. Combining the parametric nature of this modelling and its possible integration with computational design techniques, the research conducted has developed a simulation tool able to guide the designer in choosing between multiple alternative technological solutions. By writing a visual programming code (VPL), a design optioneering algorithm has been set up in order to perform technological choices. The method was applied to a horizontal partition towards an unheated space and to a vertical perimeter wall. The instruments used belong to the Autodesk Revit suite: Dynamo and Project Refinery, used for code implementation and iteration, respectively. The global outputs considered were the thickness, surface mass, thermal transmittance, cost and global warming potential (GWP) of the proposed stratigraphies. Part of the script was dedicated to verifying intertial condensation in relation to the local climate conditions.

Scientific Innovation and Relevance

(max 200 words)

The construction of sustainable buildings forces the designer to make choices that generally lead to compromise solutions between structure, energy and economy issues. The application of computer and digital approaches is particularly suitable for such multifactorial optimization problems. The availability of new software easily manageable even by non-experts contributed significantly to the implementation of optimization techniques in the building industry. However, most of the studies in literature focus on the overall energy analysis of the buildings under consideration. Instead, the research proposes a methodology that can considerably simplify the decision-making process through generative design techniques. The latter, although not yet fully experimented in engineering, allow to exploit the computational potential of modern computers for comparative analysis between several alternative solutions otherwise not confrontable. The VPL script was designed and written entirely autonomously and therefore no specific reference can be found in literature. The possibility to filter the generated solutions allows to evaluate different and often conflicting aspects in order to better respond to different needs, especially in the preliminary design stage.

Preliminary Results and Conclusions

(max 200 words)

For the floor, made with a lightened reinforced concrete slab, 4 variants of thermal insulation (EPS, XPS, wood fiber, rock wool) and 5 different thicknesses (4-6-8-10-12 cm) were considered, leading to the elaboration of 400 alternatives. After discarding solutions with high GWP index values an additional filter was applied to exclude configurations with too high thicknesses and reduced thermal trasmittance values. The most suitable stratigraphy was the one using a double layer of wood fiber for insulation, although 25% more expensive than tradional solutions. For the perimeter wall, a stratigraphy consisting of an external advanced screen façade with stone covering, thermal insulation, reinforced concrete partition and gypsum-fibre false-wall has been hypothesized. For the external insulation, the use of aerogel was tested in addition to EPS, rock wool and glass wool but then excluded due to the high costs. On the inner side, the comparison involved the construction of a thermo-acoustic insulation layer (rock wool or glass wool) or the maintenance of a gap in the false-wall. Among the 360 different stratigraphies proposed, the solution with rock wool on both sides is the best compromise.

Main References

(max 200 words)

• Cecconi, Fulvio Re, Lavinia C. Tagliabue, Sebastiano Maltese, and Martina Zuccaro, ‘A Multi-Criteria Framework for Decision Process in Retrofit Optioneering through Interactive Data Flow’, Procedia Engineering, 180 (2017), 859–69 <https://doi.org/10.1016/j.proeng.2017.04.247>

• Evins, Ralph, ‘A Review of Computational Optimisation Methods Applied to Sustainable Building Design’, Renewable and Sustainable Energy Reviews, 22 (2013), 230–45 <https://doi.org/10.1016/j.rser.2013.02.004>

• Marzouk, Mohamed, Shimaa Azab, and Mahmoud Metawie, ‘BIM-Based Approach for Optimizing Life Cycle Costs of Sustainable Buildings’, Journal of Cleaner Production, 188 (2018), 217–26 <https://doi.org/10.1016/j.jclepro.2018.03.280>

• Pavan, A, C Mirarchi, and M Giani, BIM: Metodi e Strumenti. Progettare, Costruire e Gestire Nell’era Digitale, Costruzioni, Architettura e Design (Tecniche Nuove, 2017) <https://books.google.it/books?id=u0GJswEACAAJ>

• Tuhus-Dubrow, Daniel, and Moncef Krarti, ‘Genetic-Algorithm Based Approach to Optimize Building Envelope Design for Residential Buildings’, Building and Environment, 45.7 (2010), 1574–81 <https://doi.org/10.1016/j.buildenv.2010.01.005>

• Vanossi, A, and M Imperadori, ‘BIM e Optioneering in Edifici S/R Di Piccola Scala BIM and Optioneering in Dry Technology Small-Scale Building’, 2015 <https://www.researchgate.net/profile/Andrea_Vanossi/publication/276410657_BIM_e_option



10:48 - 11:06

Uncertainty analysis of building energy analysis based on replicated Latin Hypercube sampling

Wei Tian1, Miaorou Jin1, Pieter de Wilde2, Xing Fu3, Jiaxin Shi1

1Tianjin University of Science and Technology, China; 2Plymouth University, UK; 3Tianjin Architectural Design Institure, China

Aim and Approach

(max 200 words)

Uncertainty analysis has been used in building energy analysis to provide robust predictions of energy performance of buildings due to inherent uncertain variables. Latin Hypercube sampling (LHS) is commonly used to obtain reliable results in order to reduce computational cost by using stratified sampling techniques. Most of previous studies apply LHS only one single time to obtain variations of energy performance of buildings. This research is focused on the comparison of one time LHS and replicated LHS to obtain more stable energy predictions for buildings. The replicated LHS generates LHS data of a sample size n with different sequences of random numbers. The results from these independent LHS data are analyzed to determine whether there are consistent uncertainty analysis results of building energy performance. A 3-storey office building is used as a case study to demonstrate the application of the replicated LHS technique. The energy simulation is carried out with the EnergyPlus program and the statistical analysis is carried out with the R computational environment.

Scientific Innovation and Relevance

(max 200 words)

The replicated LHS technique can provide more robust results in comparison with one time LHS in building energy analysis by providing proper comparison results from these different LHS data. The visualization of uncertainty analysis results can be plotted from the CDF (cumulative distributions functions) of heating and cooling energy data to evaluate the similarity or difference from these various LHS samplings. Formal statistical results of confidence intervals for building energy can be also derived by assuming a t-distribution for different independent LHS results to assess the convergence of uncertainty analysis. Moreover, additional sampling results can easily be added in uncertain analysis of building energy using this replicated LHS methods since the LHS data are independent each other. This replicated sampling technique can be also used for sensitivity analysis to properly determine the convergence of a ranking importance of factors influencing building energy performance.

Preliminary Results and Conclusions

(max 200 words)

The replicated LHS can provide reliable estimation of the uncertainty prediction performance of buildings by running several independent samplings. In contrast, the energy results from one time LHS may be unstable for a small sampling number. The sample size and the replicated number for using the replicated LHS method in building energy analysis can be determined by several factors, including number of input variables, relationships between inputs and outputs, and requirement for sampling convergence. A small number of LHS sampling combined with several independent LHS data is recommended to provide convergence information of uncertain energy performance analysis of buildings. Final analysis can be conducted by combining all the LHS sampling data to provide better results. Further analysis is required to understand the combining effects of various LHS methods, such as optimal and augmented sampling.

Main References

(max 200 words)

[1] Hansen C W, Helton J C, Sallaberry C J. Use of replicated Latin hypercube sampling to estimate sampling variance in uncertainty and sensitivity analysis results for the geologic disposal of radioactive waste. Reliability Engineering & System Safety, 2012, 107: 139-148.

[2] Tian W, Heo Y, de Wilde P, et al. A review of uncertainty analysis in building energy assessment. Renewable and Sustainable Energy Reviews, 2018, 93: 285-301.

[3] Li H, Wang S, Coordinated robust optimal design of building envelope and energy systems for zero/low energy buildings considering uncertainties, Applied Energy, 2020, 265:114779.

[4] Ina De Jaeger, Glenn Reynders, Dirk Saelens, Quantifying Uncertainty Propagation For The District Energy Demand Using Realistic Variations On Input Data, IBPSA 2019, Rome, Italy, September 2-4, 2019.

[5] Adrian Chong, Song Chao, A Framework For The Continuous Calibration Of Building Energy Models With Uncertainty, IBPSA 2019, Rome, Italy, September 2-4, 2019.

[6] Pang Z, O'Neill Z, Li Y, et al. The role of sensitivity analysis in the building performance analysis: A critical review. Energy and Buildings, 2020, 209: 109659.



11:06 - 11:24

Quality check of openBIM input data for thermal building simulation based on mvdXML

Andreas Geiger, Karl-Heinz Häfele, Veit Hagenmeyer

Karlsruhe Institute of Technology, Germany

Aim and Approach

(max 200 words)

Today, Building Information Modelling (BIM) covers many domains of the building life cycle. More and more software tools in the area of building performance simulation support BIM by importing openBIM data according to the buildingSMART standard Industry Foundation Classes (IFC).

However, success and quality of building performance simulations depends strongly on quality, completeness, and consistency of BIM data. Therefore, it is necessary to check in this sense the content of openBIM data before transferring it into a respective simulation tool.

To describe data exchange scenarios in general, Model View Definitions (MVD) allow the definition of subsets of the corresponding IFC data model and enforce certain IFC attributes or types to be mandatory. With Model View Definition XML (mvdXML) – also provided by buildingSMART – MVDs can be formalized and therefore are testable by software tools.

The present paper introduces a first approach for MVD rulesets to cover exchange requirements for thermal building simulations, including formalizing the MVD ruleset as mvdXML. To verify and apply these rules, an additional module for the in-house software tool IFCExplorer is developed. This module can load, edit, save and check mvdXML rules. One key focus of the development is the representation of the checking results.

Scientific Innovation and Relevance

(max 200 words)

Parallel to the development of IFC4, buildingSMART has developed mvdXML as a neutral and machine-readable format for the documentation of model view definitions (MVD). An MVD represents a subset of an IFC scheme for a specific use case, in order to ensure a reliable exchange of information for specific requirements. With ReferenceView and DesignTransferView, buildingSMART provides two official MVDs for IFC4. Since 2013, the mvdXML format additionally supports validation functionality. However, it turns out that the functional scope of mvdXML is not sufficient for some practical requirements.

For instance, the official buildingSMART MVDs are not designed for the requirements of thermal building simulations. They are missing most of the relevant rules to ensure that a simulation can be performed. Even applying all rules supported by mvdXML, there are certain limitations in checking the IFC models.

The present paper analyzes the requirements that must be fulfilled to use an architecture model for a thermal building simulation. The current version of mvdXML is evaluated on whether these requirements can be met using the existing rule syntax. Limitations of the this mvdXML version are shown. Corresponding extensions of the mvdXML standard are proposed and verified by a reference implementation in the tool IFCExplorer.

Preliminary Results and Conclusions

(max 200 words)

Target of the current research is to set up an integrated workflow for thermal building simulations based on openBIM architectural models. One important module of this workflow is the quality check of openBIM architectural input data. By developing this module, the following results are achieved and are discussed in the present paper:

• Concept of a Model View Definition and an initial set of requirements,

• Manual generation of the corresponding mvdXML,

• Implementation of the mvdXML rule checking engine in the software tool IFCExplorer,

• Presentation of the checking results in an interactive way.

All results are in a prototypical stage. The implementation shows that the current mvdXML specification is not covering all requirements for a comprehensive model check. Proposals for extensions of mvdXML are collected and will be introduced to the mvdXML developer group. The checking engine can process all major rule types. Particular attention is paid to the reporting of the test results. To interpret and evaluate the results, no specific knowledge of MVD and mvdXML should be necessary.

The functionalities of the module are demonstrated with a selection of openBIM models of existing buildings.

Main References

(max 200 words)

[1] - Chipman, T., Liebich, T., Weise, M., 2016, „Specification of a standardized format to define and exchange“, buildingMSART International Ltd., 15.02.2016

[2] - Liebich, T., Geiger, A., Katranuschkov, P., Linhard, K., Steinmann, R., Weise, M., 2011, „mvdXML specification, mvdXML Schema“, buildingSMART International

[3] - Weise, M., Nisbet, N., Liebich, T., Benghi, C., 2016, „IFC model checking based on mvdXML 1.1”

[4] - Hietanen, J., 2006, „IFC model view definition format“, buildingSMART International

[5] - ISO 16739. 2018. ISO 16739:2018 Industry Foundation Classes (IFC) for data sharing in the construction and facility management industries. 2018



11:24 - 11:42

Cross-over analysis of building-stock modelling approaches for bottom-up engineering model

Usama Bin Perwez, Yohei Yamaguchi, Yoshiyuki Shimoda

Osaka University, Japan

Aim and Approach

(max 200 words)

In building stock modelling (BSM), several methodologies have been developed to quantitatively improve the robustness and the consideration of heterogeneity of building stocks but most of these studies have not focused on identifying the impact of these methodologies on the performance of urban building energy models (UBEMs). To further understand the limitations of various building stock modelling methodologies, this paper presents the evaluation of three building stock modelling methodologies, geo-referenced [1], sample-based and sample-free models [2][3][4], to assess the accuracy and added-value of these approaches for use in bottom-up engineering model. The first method uses geographical information systems (GIS) to incorporate geo-referenced dataset within the model, while other two methods follow a synthetic approach by using iterative proportional fitting (IPF) [5] and Monte Carlo random sampling [6] to generate sample-based and sample-free building stocks respectively. These methods have been implemented on Tokyo commercial building stock as a case study, to further explore the strategies to overcome the limitation of uncertainty and availability of data in the implementation of UBEM.

Scientific Innovation and Relevance

(max 200 words)

To the best of the author’s knowledge, this study presents a comparison of three major building stock approaches for the first time. The study points out the advantages and disadvantages of synthetic building stock approaches in comparison to a GIS-based building stock approach by using detailed dynamic building simulation tool. The study aims to contribute to the literature development by:

1. To quantify the accuracy and added-value of these building stock modelling approaches for use in bottom-up engineering model.

2. To provide a granular level framework in choosing the right building stock modelling approach by assessing the availability (or uncertainty) of data at either aggregated or disaggregated level.

3. To demonstrate the use of these approaches in predicting the energy demand and GHG emissions of the commercial building stock of Tokyo, Japan.

Preliminary Results and Conclusions

(max 200 words)

This study has focused to determine the accuracy and added value of the building stock modelling approaches, in terms of heterogeneity, data dimensionality, integration and non-linear interactions within stock, for use in bottom-up engineering model. The building stock modelling methodologies are implemented for the commercial building stocks (office, retail, school, hotel and hospital segments) of Tokyo, to evaluate the cross-sectional and longitudinal enrichment of building attributes and heating, ventilation, and air-conditioning (HVAC) stock. The preliminary results show that sample-free synthetic approach can incorporate multiple input distributions (building age and material stock) using building census or survey data, while geo-referenced approach provides additional key determinants such as building typology (shape coefficient and indices) and urban morphological attributes. This shows that synthetic approach can be extended to commercial building stock, which mostly has a poorer data availability than residential building stock, that further allows to encompass modelling of a typical mixed-use urban environment. Moreover, this cross-over analysis will provide a granular level framework to assist the city level planners and policy makers in choosing the right building stock modelling approach for predicting the energy demand and GHG emissions of the commercial building stock.

Main References

(max 200 words)

1) M. Österbring, É. Mata, L. Thuvander, M. Mangold, F. Johnsson, H. Wallbaum: A differentiated description of building-stocks for a geo referenced urban bottom-up building-stock model, Energy and Buildings, Vol. 120, pp. 78-84, 2016.

2) K. Hermes, M. Poulsen: A review of current methods to generate synthetic spatial microdata using reweighting and future directions, Computers, Environment and Urban Systems, Vol. 36, Issue 4, pp. 281-290, 2012.

3) M. Lenormand, G. Deffuant: Generating a synthetic population of individuals in households: sample-free vs sample-based methods, J. Artif. Soc. Soc. Simul., Vol. 16, pp. 1–10, 2013.

4) C. Nägeli, C. Camarasa, M. Jakob, G. Catenazzi, Y. Ostermeyer: Synthetic building stocks as a way to assess the energy demand and greenhouse gas emissions of national building stocks, Energy and Buildings, Vol. 173, Pages 443-460, 2018.

5) R. Beckman, K. Baggerly, M. McKay: Creating synthetic baseline populations, Transportation Research Part A: Policy and Practice, Vol. 30, Issue 6, pp. 415-429,1996

6) F. Gargiulo, S. Ternes, S. Huet, G. Deffuant: An Iterative Approach for Generating Statistically Realistic Populations of Households, PLOS ONE 5(1): e8828, 2010.



11:42 - 12:00

Automatic IFC data enrichment with space geometries for Building Energy Performance Simulations

Georgios Nektarios Lilis, Kyriakos Katsigarakis, Dimitrios Rovas

University College London, London, UK

Aim and Approach

(max 200 words)

Recently, there is an increased attention to methods for automatic building energy performance simulation (BEPS) model generation from building information models (BIMs) for evaluation of building retrofitting scenarios [1]. These BEPS models require information on the geometry of the building space volumes for correct second-level space boundary topology generation [2], [6]. Sometimes, this space volume geometrical information is incorrectly defined or not defined at all in the building information models. The present work introduces an algorithm for the generation of the geometric representation of the building space volumes from their surrounding architectural building elements defined in the BIMs. The algorithm has three stages. Initially, the boundary representations of all architectural building elements (walls, slabs, …) are extracted from their geometric representations. In the second stage, the common boundary surfaces of these representations are calculated. Finally, by subtracting the common boundary surfaces, from the boundary representation surfaces, the first-level space boundary surfaces [6] are obtained. These first-level space boundary surfaces are merged to form the internal building space geometrical representations.

Scientific Innovation and Relevance

(max 200 words)

Attempts for building space volume extraction from 3D building models using graph methods have been documented [3]. Here a novel approach based on BIMs conforming to the International Foundation Class 4 (IFC4) standard [4] is introduced. The deserialization of the IFC4 models are performed using a purpose-built library; in addition, a geometric library has been developed for boundary representation generation and dedicated geometric operations. The space definitions can be quite useful for a number of cases, including the process of automating the energy model generation. The algorithm generates the internal building space volumes using the physical obstructions (walls, slabs, ...) as space separation boundaries and supports linear as well curved surrounding constructions. Possible user or IFC exporter errors using manual building space definitions can be also avoided by the use of the introduced process. The remaining surfaces of the boundary representations of the building constructions after their common boundaries and first-level space boundary surfaces are removed, form an outer building shell which is essentially the building facade. Finally, the obtained first-level space boundary surfaces [6] are used together with the BIM library to enrich the input IFC4 file with the building space geometrical representations.

Preliminary Results and Conclusions

(max 200 words)

To guarantee accurate results, an important prerequisite of the introduced algorithm is that the input BIM IFC4 file is geometric error-free i.e. all boundary representations of the architectural elements have no missing surfaces and they do not intersect with each other [5]. If intersections (clashes) among building conclusions exist, the common edges of the first-level space boundary surface near the area of the clash, cannot be defined and therefore the boundary representations of the respective building spaces cannot be reproduced. Finally, a missing surface in the boundary representation of an architectural element, will result in a missing surface in the first-level space boundaries and the respective building space volumes and therefore should be detected and corrected. To illustrate the broad applicability, the method is tested on real complex building cases. Apart from the internal building space volumes the technique also identifies the external facade surfaces of the investigated buildings. The development of the introduced algorithm is supported by the H2020 research project BIMERR.

Main References

(max 200 words)

[1] Giannakis, G. I., Katsigrakis, K. I., Lilis, G. N., & Rovas, D. V. (2019) “A Workflow for Automated Building Energy Performance Model Generation Using BIM Data”, Building Simulation conference of IBPSA.

[2] Lilis, Georgios N., Georgios I. Giannakis, and Dimitrios V. Rovas. (2017) "Automatic generation of second-level space boundary topology from IFC geometry inputs."Automation in Construction 76: 108-124.

[3] van Treeck, Christoph, and Ernst Rank. (2017) "Dimensional reduction of 3D building models using graph theory and its application in building energy simulation."Engineering with Computers 23.2:109-122.

[4] Liebich, Thomas. (2013) "IFC4—The new buildingSMART standard." IC Meeting. Helsinki, Finland: bSI Publications.

[5] Lilis, G. N., Giannakis, G., Katsigarakis, K., & Rovas, D. V. (2018). A tool for IFC building energy performance simulation suitability checking. In Proc. 12th European Conference on Product andProcess Modelling (ECPPM) (pp. 57-64).

[6] Bazjanac, V. (2010). Space boundary requirements for modeling of building geometry for energy and other performance simulation. In CIB W78: 27th International Conference.

 
10:30 - 12:00Session W1.8 (Online Track): Buildings paving the way for the energy transition
Location: Virtual Meeting Room 2
Session Chair: Yoshiyuki Shimoda, Osaka University
Virtual Meeting Room 2 
 
10:30 - 10:48

Projecting impacts of uncertain climate change on future energy demand

Sandhya Patidar, David Jenkins, Andrew Peacock

Heriot-Watt University, United Kingdom

Aim and Approach

(max 200 words)

Energy demand in future is very likely to be impacted by various uncertain changes occurring in our society, such as technological growth, user behaviour, government policy, industrial strategies and climate change [1]. Climate change is one of the key factors effecting the future energy demand, e.g., warming climate could influence winter heating demand and/or summer air-conditioning demand [2]. This paper aims to develop a hybrid system of novel data-driven approaches for conducting an in-depth analysis (evaluating the magnitude) of the impacts of climate change and associated uncertainty on energy demand at both residential and community-level. The new approach is calibrated at a level of individual building demand profile to simulate future-morphed synthetic profiles that can be scaled up to realise, and visualised, the impact in aggregated profiles of communities in a manner that could reflect how individual dwelling profiles might respond to various future scenarios, and how this might be quantified at a regional, community level.

Scientific Innovation and Relevance

(max 200 words)

To attain optimum efficiency, the underpinning modelling approaches will adopt a hybrid structure that will integrate carefully selected cutting-edge statistical, mathematical and machine learning based data processing/modelling approaches. The innovative design of hybrid system involves statistical time-series decomposition technique (STL: A Seasonal –Trend Decomposition procedure based on Loess processes [3]) for extracting trend, seasonal and random components from energy demand and corresponding climatic (e.g. temperature) time-series. The seasonal components of demand and climatic series are processed using wavelet power spectrum analysis. Application of wavelet analysis is strategically intended for identifying and extracting highly significant periodic signals (features) from the seasonal components. The periodic features drawn from the climatic and demand series are used to calibrate a ‘Climate module’ based on widely applied machine learning algorithm Support Vector Regression (SVR) [4]. The climate module within the hybrid system is designed for projecting the impacts of seasonal/periodic climatic feature on the corresponding seasonal features in demand series. Finally, a demand synthesis module, referred to as HMM-GP [5], that involves a Hidden Markov Model (HMM) coupled with an extreme-value distribution, Generalised Pareto (GP), is integrated within the hybrid system for generating future morphed synthetic demand profiles.

Preliminary Results and Conclusions

(max 200 words)

To demonstrate the potentials of the proposed hybrid system, a small community village, Fintry based in Stirlingshire (Central Scotland), is selected [6]. For the present study electricity demand data available across 115 participating households in the community of (~350 households) at 15- and 30-minute resolution are used. The hybrid system is applied to a small selection of sample buildings from the case-study community to generate several statistically synchronous future-morphed synthetic demand series. These future-morphed simulated series are aggregated to generate community-level demand profiles for future climate change scenarios. A k-mean clustering approach (using statistical mean/median of total demand as key features) is applied to group the buildings in the community. Selection of the sample is weighted proportionally to the size of the clusters, for both sampling and aggregation purpose, to ensure the outputs represent adequate diversity across the community. Climate projection from the UKCP18 database [7] is utilised within the climatic module to generate climate-informed demand series and to explore climatic uncertainty in future energy demand at community-level. The results are thoroughly analysed and validated using appropriate statistical measures, such as box plots, probability density distribution, percentile distribution and autocorrelation function.

Main References

(max 200 words)

[1] “Updated energy and emissions projections,” HM Government, 2017.

[2] T. Rogers-Hyden, F. Hatton and I. Lorenzoni, “‘Energy security’ and ‘climate change’: Constructing UK energy discursive realities,” Global Environmental Change, vol. 21, no. 1, pp. 134-142, 2011.

[3] R. B. Cleveland, W. S. Cleveland, J. E. McRae and I. Terpenning, “STL: A Seasonal-Trend Decomposition Procedure Based on Loess,” Journal of Official Statistics, vol. 6, no. 1, pp. 3-73, 1990.

[4] M. Awad and R. Khanna, “Support Vector Regression,” in Efficient Learning Machines, Berkeley, CA, Springer, Apress, 2015, pp. 67-80.

[5] S. Patidar, D. P. Jenkins, A. Peacock and P. Mccallum, “Time Series Decomposition Approach for Simulating Electricity Demand Profile,” in Building Simulation 2019, 16th IBPSA International International Conference, Rome, Italy, 2019.

[6] J. Smith, “http://smartfintry.org.uk/about-smart-fintry/resources/,” Smart Fintry, 13 04 2018. [Online]. Available: http://smartfintry.org.uk/wp-content/uploads/2018/04/Smart-Fintry-Innovation-Report-final.pdf. [Accessed 07 2020].

[7] “UK Climate Projections (UKCP18),” Met Office Hadley Centre Climate Programme, UK, 2018.



10:48 - 11:06

Analysis of the energy performance of a new ventilated brick wall: behaviour of real scale prototype under different ventilation configuration and weather conditions

Costanza Vittoria Fiorini1, Domenico Palladino2, Cinzia Buratti3

1CIRIAF, University of Perugia, Via G. Duranti 63, 06125 Perugia, Italy; 2ENEA, Italian National Agency for New Technologies, Energy and Sustainable Economic Development of Engineering, Via Anguillarese, 301, 00123 Rome, Italy; 3Department of Engineering, University of Perugia, Via G.Duranti 67, 06125 Perugia, Italy

Aim and Approach

(max 200 words)

Ventilated façade allows to reduce thermal loads during the cooling period.

This work aims to assess the thermal behavior of a ventilated wall with high thermal inertia, made of local construction materials.

According to results obtained at laboratory scale, a real prototype of the ventilated façade was built as a perimeter wall of a gym.

Openings, 250x25 mm2/m of horizontal length, are placed at the bottom and at the top of the wall. Its height, 8.50m, allows to increase the flow rate within the air gap, thanks to the stack-effect.

The southern façade is equipped to monitor air and surface temperature, air velocity, heat flux.

Three experimental campaigns were carried out in winter and summer period with close, partially close, and open holes, with the following aims: comparing non-ventilated, partially ventilated, and ventilated configuration; evaluating the height influence on the temperatures within the ventilation gap and highlighting the potential phase displacement between those temperatures and the outdoor air temperature; monitoring the temperature and air velocity fields in the air gap and inside/outside, in order to evaluate the energy performance of the ventilated wall during two years of monitoring; using experimental results to implement and validate a 3D-CFD model.

Scientific Innovation and Relevance

(max 200 words)

Given the impossibility of correctly assessing the thermal transmittance of this type of wall through the methodology provided by the current reference legislation, the research is aimed at evaluating the in-situ behavior of a real scale prototype, taking into account how the number and position of the openings affect its performance. Openings configuration was first optimized on a prototype of masonry ventilated wall built at laboratory scale and the experimental data monitored on it allowed the validation of a 3D CFD simulation model.Implementation and validation of a new 3D CFD model with experimental results at real scale (indoor/ outdoor air temperature, surface and air-gap temperature) will allow to predict the behaviour of the wall in different periods of the year and in different climate conditions, in order to establish the real benefit of the ventilation. Results related to conventional wall and innovative brick ventilated wall, in terms of energy demand, will be compared both in different cities and climatic conditions. Also in suggesting a ventilated wall made by traditional and local materials lies the peculiarity of this purpose: such a solution guarantees thermal comfort maintaining the constructive tradition (of Umbria region), both for new buildings and for refurbishment interventions.

Preliminary Results and Conclusions

(max 200 words)

Non-ventilated, partially-ventilated and ventilated wall in winter case inside the cavity have surface temperatures and air temperature curves overlapping.

For partially-ventilated configuration cavity temperatures never reach the external peaks, departing from them of about 3°C, allowing heat losses reduction during the heating hours.

Ventilation configurations affect air temperature profiles in the cavity, with an almost linear trend as the height increases, according to stack-effect. For the ventilated configuration in the coldest hours the temperature is higher in the upper part of the wall, in the warmest at 3.55m and 6.5m. At the bottom (2.55m) the lowest temperatures are generally recorded.

In summer conditions inside the cavity the air temperature deviates from the surface ones up to 5°C, following the course of the external temperature in a smaller range (15°C and 20°C respectively), especially at lower temperatures.

Outdoor/indoor air temperatures phase displacement is 1.30 h in the night period and 3 h in the day period. During the daytime the counter-wall maintain low surface temperatures on the inner wall of the cavity: up to 4.5ºC lower than the external.

Summer difference between average flow values for ventilated and partially-ventilated wall is 8 W/m2: the first one guarantees optimal disposal.

Main References

(max 200 words)

[1] Buratti, C., Palladino, D., Moretti, E., Di Palma, R., 2018. Development and optimization of a new ventilated brick wall: CFD analysis and experimental validation. Energy Build. 168, 284–297.

[2] Gagliano, A., Aneli, S., 2020. Analysis of the energy performance of an Opaque Ventilated Façade under winter and summer weather conditions. Solar Energy 205, 531-544.

[3] Liu, L., Yu, Z., Zhang, H., 2017. Simulation study of an innovative ventilated facade utilizing indoor exhaust air. In: International Conference on Improving Residential Energy Efficiency, IREE 2017.

[4] C. Marinoscia , G. Semprinia , G.L. Morini , Experimental analysis of the summer thermal performances of a naturally ventilated rainscreen façade building, En- ergy Build. 72 (2014) 280–287 .

[5] S. Saadon , L. Gaillard , S. Giroux-Julien , C. Ménézo , Simulation study of a naturally-ventilated building integrated photovoltaic/thermal (BIPV/T) envelope, Renew. Energy 87 (2016) 517–531 .

[6] C. Buratti , D. Palladino , E. Moretti , Prediction of indoor conditions and thermal comfort using CFD simulations: a case study based on experimental data, Energy Procedia 126 (2017) 115–122 .



11:06 - 11:24

Development of an urban sewage state prediction model and case studies for the evaluation of sewage heat utilization potential

Weian Chen1, Shohei Miyata2, Yasunori Akashi2

1National Kaohsiung Normal University, Kaohsiung, Taiwan; 2University of Tokyo, Japan

Aim and Approach

(max 200 words)

Sewage heat is a stable heat source for heating and hot water supply through the heat pump due to its small temperature fluctuation affected by season [1]. The utilization of sewage heat is a novel issue within the field of the development of renewable energy, especially the technique of recovering the heat through pipelines [2–5] in a regional scale to maximize heat reutilization by buildings [2,6]. However, the features and utilization potential of sewage heat have not been completely explored so far [7,8]. Therefore, there is still the possibility to draw up better sewage heat utilization plans and strategies to efficiently exploit the heat in urban areas, owing to its high penetration rate of the sewer system, and eventually reduce the environmental load.

This study aims at suggesting an estimation methodology and judging criteria based on an urban sewage state prediction model to evaluate the sewage heat utilization potential in an urban area and recommended utilization objects. In this paper, the evaluation methodology is introduced through case studies that applied the model to an actual area for evaluating the regional sewage heat utilization potential and clarifying which building is proper to utilize the sewage heat.

Scientific Innovation and Relevance

(max 200 words)

An urban sewage state prediction model is proposed in the study, which can predict the sewage state and conduct the regional simulation for evaluating the sewage heat utilization potential to make the regional optimal utilization of sewage heat. Specifically, because the model can be applied to the areas as long as certain statistical databases (original water consumption unit, hot and tap water consumption unit, etc.) and GIS data (building and pipe information) are prepared, the measurement data of sewage flow rate and temperature are not essential in this model; therefore, the estimation method can be adapted to not only existed areas but new areas which are still under planning and drawing up the proper regional energy utilization plan.

This model can simulate the entire circulation from the energy supply side to the demand side, which including sewage physical model and sewage heat utilization system model. The two models were both established from the perspective of the features of heat rejection and heat demand of different building types. Comprehensively, it is expected to apply the model to discuss sewage heat utilization potential in an urban scale; moreover, the relationship between building spatial distribution and their energy consumption can also be clarified.

Preliminary Results and Conclusions

(max 200 words)

The application of this model is first applied to an actual urban area to simulate the comprehensive utilization potential under different utilization rates. Specifically, without considering the particular strategies, the model is attempted to apply to an entire area for confirming its feasibility at the initial step, and clarified the approximate regional sewage heat utilization potential. Regarding the result, while the penetration rate of sewage heat utilization system is 80 %, the regional sewage heat utilization potential can achieve the greatest effect for about 10.69%. It shows that there is an abundant amount of sewage heat existed in the urban area that can be broadly utilized by more buildings. However, there is still a limitation that excessive utilization may lead to the worse effect; For instance, when the penetration rate is 100%, the utilization potential is 10.38%, which is lower than the result of 80%.

Secondly, from the practical view, we focus on specific buildings to compare which objective building is recommended to utilize the sewage heat in priority according to its better energy-saving effect and higher performance of sewage heat utilization system. Briefly, the relationship between different building location and their energy consumption, heat pump COP are analyzed.

Main References

(max 200 words)

[1] Ministry of Land, Infrastructure, Transport W management department SD. Sewage heat utilization manual. 2015.

[2] Ichinose T. et al., Regional feasibility study on district sewage heat supply in Tokyo with geographic information system. Sustain Cities Soc 2017;32:235–46.

[3] Culha O. et al., Heat exchanger applications in wastewater source heat pumps for buildings: A key review. Energy Build 2015;104:215–32.

[4] Dürrenmatt DJ, Wanner O. Simulation of the wastewater temperature in sewers with TEMPEST. Water Sci Technol 2008;57:1809–15.

[5] Cui L. et al., Study of sewage heat utilization and heat interchange system that utilizes a network of sewer lines in urban areas (part 14 study of sewage heat amount available). vol. 10, 2014.

[6] Zhang C. et al., Design generalization of urban sewage source heat pump heating and air conditioning engineering. Proc - 3rd Int Conf Meas Technol Mechatronics Autom ICMTMA 2011 2011;1:926–9.

[7] MIKE M. et al., The Evaluation of Sewage Temperature and Flow Rate for Estimating Sewage Temperature and Flow Rate in Sewer Line. Trans Soc Heating, Air-Conditioning Sanit Eng Japan 2014;39:11–21.

[8] Cipolla SS. et al., Heat recovery from urban wastewater: Analysis of the variability of flow rate and temperature. Energy Build 2014;69:122–30.



11:24 - 11:42

Investigating the control strategies for Breathing Walls during summer: a dynamic simulation study

Andrea Alongi, Adriana Angelotti, Livio Mazzarella

Politecnico di Milano, Italy

Aim and Approach

(max 200 words)

The paper aims to study different strategies for the optimal operation of Breathing Walls during summer. The investigation is carried out by performing dynamic simulations on a case study. To this purpose, a transient Finite-Difference numerical model for Breathing Wall components, previously developed in Matlab and validated by the Authors in [1], is coupled with TRNSYS. The case study consists in an office room located in Milan, Italy, provided with Air Conditioning and Mechanical Ventilation and with an air permeable wall.

Scientific Innovation and Relevance

(max 200 words)

The best operation strategy for Breathing Walls in heating dominated climates is almost assessed: it consists in forcing the ventilation air across the permeable walls and roof in order to pre-heat it. Conversely, the optimal use of Breathing Walls in cooling conditions still needs to be explored: some Authors suggested the so-called Exhaust Air Insulation mode [2], namely forcing exhaust air from the indoor environment across the Breathing Walls to reduce envelope heat gains, some others proposed coupling with night free cooling [3]. In addition, pre-cooling of the ventilation air by flowing across the Breathing Walls may be considered. Therefore, the scientific relevance of the paper consists in clarifying the best summer use of this technology in the given context and proposing a control strategy for the airflow direction.

Moreover, the study features the integration of a model specifically developed for Breathing Wall components with an existing BES tool (TRNSYS), which has never been done before. This allows to perform a comprehensive building simulation, where the Breathing Wall can properly be simulated at the same time as a building envelope component and as a part of the mechanical ventilation system.

Preliminary Results and Conclusions

(max 200 words)

Preliminary results of the simulations show that the best operation strategy depends on the characteristics of the room cooling load, namely the relative importance of ventilation load compared to transmission load. Moreover, a key parameter that should be firstly evaluated is the heat recovery efficiency of the Breathing Wall, to be compared with the efficiency of the heat recovery exchanger in case present.

Main References

(max 200 words)

[1] Alongi A, Angelotti A, Mazzarella L. A numerical model to simulate the dynamic performance of Breathing Walls, submitted to: Journal of Building Performance Simulation.

[2] Wang J., Du Q., Zhang C., Xu X., Gang W. (2018). Mechanism and preliminary performance analysis of exhaust air insulation for building envelope wall. Energy & Buildings (173) 516-529.

[3] Ascione F, Bianco N and De Stasio C. Dynamic insulation of the building envelope: numerical modelling under transient conditions and coupling with nocturnal free cooling. Appl Therm Eng 2015; 84: 1–14.



11:42 - 12:00

An evaluation of the proposed framework to introduce a smart readiness indicator for buildings

Vasiliki Varsami, Esfand Burman

Institute for Environmental Design and Engineering, University College London (UCL), United Kingdom

Aim and Approach

(max 200 words)

The Energy Performance of Buildings Directive was amended in 2018. A key objective was to promote the development of smart buildings since they were considered key enablers for future energy grids and systems. In this revision, the Directive called for the development of a new Smart Readiness Indicator (SRI) for buildings. The indicator is expected to provide a common framework across Europe, which evaluates the capacity of a building to use information and communication technologies in order to adapt to the needs of the occupants and the grid.

Although the scheme is not finalised, researchers and industry practitioners have already raised many questions about the methodology and the fair application of the scheme across all European Member States.

This paper reviews the proposed smart-readiness framework and assessment methods. Additionally, data from two existing non-residential buildings have been used to investigate the impact of the simplified and detailed methodologies defined for SRI on the final rating. Through this research and application of the scheme, the study aims to evaluate the strengths and improvement opportunities of the SRI framework and its role on enhancing building performance.

Scientific Innovation and Relevance

(max 200 words)

An ongoing second technical study is finalising the newly proposed framework that is expected to measure the capability of buildings to respond efficiently to the external environment and the demand of the occupants. The scheme has the potential to offer multiple benefits, from improving occupants’ well-being to promoting interconnected building communities and smart grids. Moreover, smart buildings can be key enablers for Europe to meet its Paris Agreement goal and keep in line with UN Sustainable Development Goals.

However, an indicator that measures capability can fail to translate into real performance. This could send a wrong message to end users reminiscent of the problem of energy performance gap and the credibility issue facing energy performance certificates. The two separate methodologies that exist may also lead to inconsistent certifications.

Therefore, the study aims to identify the potential issues that may rise up during the introduction of the indicator to the industry and can hinder the success of the scheme as well as improvement opportunities. By doing so, the paper can inform the process of continuous improvement of the scheme and demonstrate how this framework could be used to improve energy efficiency, energy flexibility and building user comfort.

Preliminary Results and Conclusions

(max 200 words)

Two large-scale, public buildings have been chosen as case studies. Both buildings have been designed with innovative, energy-efficient systems but have different environmental approaches and energy needs.

After calculating their smart readiness indicator score using both the simplified and detailed proposed methodology, the results have shown an approximate 10% difference between the two methods. Regarding energy performance, no correlation between the smart readiness results and energy performance of the case studies has been identified. Subsequently, the weighted factors where adjusted according to simulation results to demonstrate how the assessment can account for the building type and climate.

The original scores were compared with results from the literature and the beta testing process of SRI. Although both buildings have been constructed in the past five years, their SRI scores are close to the mean value for non-residential buildings. In particular, of the three key functionalities that smart readiness assesses, namely, energy efficiency, energy flexibility, and response to user needs, both cases scored very low (around 18%) on energy/grid flexibility. By having such a strong focus on demand control and grid integration, the scheme has the potential to promote grid flexibility in buildings and pave the way for future electricity markets.

Main References

(max 200 words)

European Commission, (2020). Discussion document – preparation of the delegated act of the smart readiness indicator. In: Meeting of the Expert Group on the Energy Performance of Buildings Directive. Brussels.

Janhunen, E., Pulkka, L., Säynäjoki, A. and Junnila, S., 2019. Applicability of the Smart Readiness Indicator for Cold Climate Countries. Buildings, 9(4), p.102.

Kurnitski, J. & Hogeling, J. (2018) Smart Readiness Indicator (SRI) for buildings not so smart as expected. REHVA Journal. (August 2018), 4.

Märzinger, T. and Österreicher, D., 2019. Supporting the Smart Readiness Indicator—A Methodology to Integrate A Quantitative Assessment of the Load Shifting Potential of Smart Buildings. Energies, 12(10).

Smartreadinessindicator.eu. (2020). Smart Readiness Indicator for Buildings. [online]

Vigna, I., Pernetti, R., Pernigotto, G. and Gasparella, A., 2020. Analysis of the Building Smart Readiness Indicator Calculation: A Comparative Case-Study with Two Panels of Experts. Energies, 13(11), p.2796.

Verbeke, S., Aerts, D., Rynders, G., Ma, Y. and Waide, P., (2020). 3rd Interim Report of the 2nd Technical Support Study on the Smart Readiness Indicator for Buildings. Brussels: VITO NV.

 
10:30 - 12:00Session W1.9 (Online Track): Ensuring high quality building simulations/BIM
Location: Virtual Meeting Room 3
Session Chair: Heba Hassan, Beni Suef University
Virtual Meeting Room 3 
 
10:30 - 10:48

Automatic generation of second level space boundary geometry from IFC models

Eric Fichter, Veronika Richter, Jérôme Frisch, Christoph van Treeck

Institute of Energy Efficiency and Sustainable Building (E3D), RWTH Aachen University, Germany

Aim and Approach

(max 200 words)

Building Information Modeling (BIM) describes a method of networked planning, execution and management of buildings using software. All relevant building data are digitally modelled, combined and recorded. To ensure a holistic planning process, it is advisable to use building models for process planning simulations. In case of an OpenBIM approach, the models can be transferred as IFC files [1]. In simulation practices, however, the models are often of poor quality. This is due to immature export functions and incomplete enrichment. In context of thermal simulations, this includes the lack of second level space boundaries within IFC models, which are necessary for simulation in EnergyPlus [2]. The consequence is a time-consuming manual rework for the simulation expert. An automated enrichment using software that is robust against geometric modelling or export errors and that does not rely on perfect meta-information would be beneficial. Therefore, the goal of this paper is to present a tool that enriches IFC files with correct second level space boundaries. The algorithm will be explained and then applied to an example building. For verification, the enriched IFC model will be simulated using EnergyPlus. The results will be compared with a manually generated simulation model.

Scientific Innovation and Relevance

(max 200 words)

In the last two decades, multiple algorithms and programs for the generation of second level space boundaries were presented and documented in literature [3, 4, 5, 6]. However, most of them are not actively supported anymore, are based on older IFC versions (for example IFC 2x3) or are not publicly accessible. Moreover, all the mentioned algorithms used closed-source libraries. In contrast, the tool presented in this paper is based on widely used and well maintained open-source libraries. Furthermore, no meta information, e.g. the definition of spaces and their relation to building elements, is needed. Nevertheless, if meta information is provided, it could also be used. By avoiding Boolean operations between volumes, the algorithm is robust against modeling errors, such as gaps and non-physical superposition of volumes. Beside the generation of the space boundaries, a watertight and simplified surface geometry is created, in which the faces of the building elements are split according to the boundaries. Moreover, the spaces are generated as well.

Preliminary Results and Conclusions

(max 200 words)

The generated space boundaries are exported to IFC. If necessary, the simplified and corrected geometries can also be exported as boundary representation in a geometry file format. The proposed method significantly reduces the manual effort for model generation and contributes to the derivation of simulation models from BIM data. Therefore, it improves the OpenBIM work process along with the design and optimization of building energy systems. In addition to the use in building energy performance simulation, an application in the pre-processing of geometry for Computational Fluid Dynamics (CFD) simulations is conceivable. The algorithm and the applications will be presented in the paper.

Main References

(max 200 words)

[1] ISO 16739-1:2018, Industry Foundation Classes (IFC) for data sharing in the construction and facility management industries — Part 1: Data schema

[2] EnergyPlus Development Team, 2020. EnergyPlus engineering reference: The reference to EnergyPlus calculations. EnergyPlus Version 9.0. US Department of Energy.

[3] van Treeck, C., Rank, E. Dimensional reduction of 3D building models using graph theory and its application in building energy simulation. Engineering with Computers 23, 109–122 (2007).

[4] Rose, C.M., Bazjanac, V. An algorithm to generate space boundaries for building energy simulation. Engineering with Computers 31, 271–280 (2015).

[5] Lilis, Georgios & Giannakis, Georgios & Rovas, Dimitrios. (2016). Automatic generation of second-level space boundary topology from IFC geometry inputs. Automation in Construction. 76.

[6] Jones, Nathaniel & McCrone, C.J. & Walter, B.J. & Pratt, K.B. & Greenberg, D.P. (2013). Automated translation and thermal zoning of digital building models for energy analysis. Proceedings of BS 2013: 13th Conference of the International Building Performance Simulation Association. 202-209.



10:48 - 11:06

Geometrical interoperability of 3D CityGML building models for urban energy use cases

Avichal Malhotra1, Yue Pan2, Jérôme Frisch1, Christoph van Treeck1

1Institute of Energy Efficiency and Sustainable Building (E3D), RWTH Aachen University, Germany; 2Nesseler Grünzig Bau Gmbh, Germany

Aim and Approach

(max 200 words)

Geographical Information Systems (GIS) are often used as the foundation for urban scale thermal simulations. Virtual 3D city models, therefore, do serve as an important entity for analysing the thermal behaviour of buildings at an urban scale. However, the geometrical and semantic information for multiple buildings are openly available only for a relatively smaller number of countries, cities and districts. CityGML [1], a XML based modelling standard, is gaining popularity for city level information modelling and simulations. State- and city-wide 3D CityGML models are also available for countries like Germany, Austria and Switzerland [2]. However, the question about the geometrical interoperability of these models is still unanswered. Within the scope of this paper, the authors will present a CityGML Geometrical Transformation and Validation tool (CityGTV). This tool does facilitate the interoperability of 3D CityGML building models for countries where no or low quality data exists. Furthermore, the CityGTV will allow simulation scientists and urban planners to efficiently transform the building coordinates, validate the geometrical aspects of the buildings and further compute the district level energy performance of the buildings using environments such as Modelica, EnergyPlus, etc. With the tool, the altitude and orientations of individual buildings can also be transform.

Scientific Innovation and Relevance

(max 200 words)

For many of the developed and developing nations, the scarcity of CityGML datasets is quite high. These countries on the other hand have a large potential for energy conservation and green energy production. Facilitating coordinate transformations of the 3D models within different reference systems, the transformed CityGML datasets can be used for multiple use cases and scenarios. Moreover, as the semantic, geometric and sometimes monitoring data availability of the existing built-up buildings is higher, transformed virtual 3D models of these buildings can be used as references for future planning and development of an urban area. One possible use case would be to analyse the solar potential of a city quarter in equatorial regions using the transformed 3D models of buildings from temperate or polar areas. Though CityGML data models only contain the geometrical and semantic information, these could be extended using the CityGML Application Domain Extensions (ADEs) [3]. For the scenario-specific analysis, the building models can be enriched using tools such as CityGML Toolbox [4] and therefore, be simulated for the individual use cases. This tool will also help urban planners and the simulation community to increase the operability of CityGML data models for multiple applications and domains.

Preliminary Results and Conclusions

(max 200 words)

The CityGTV tool is currently being developed using python programming and PyQT [5] schema bindings. The user-friendly architecture and interface of the tool will allow users of different expertise levels to easily transform the building model(s) to their required reference systems. Within the tool the functionalities of geometrical validation and visualization are also foreseen by the authors. In future, the CityGTV tool will undergo an open source development process. The object oriented development methodology adapted by the authors will also facilitate the integration of CityGTV into different tool chains and simulation environments. The current implementation of the tool is being rigorously tested and further developed using open source datasets of large city quarters from cities such as Hamburg, Vienna, Berlin, etc. The transformed building models can be exported as new CityGML datasets which are in the user defined coordinate reference system.

Main References

(max 200 words)

[1] G. Gröger, T. Kolbe, C. Nagel und K. Häfele, „OGC City Geography Markup Language (CityGML) Encoding Standard,“ OGC, 2012.

[2] A. Malhotra, J. Bischof, J. Allan, J. O'Donnel, T. Schwengler, J. Benner und G. Schweiger, „A review on country specific data availability and acquisition techniques for city quarter information modelling for building energy analysis,“ in Forthcoming IBPSA BauSIM 2020, Graz, 2020.

[3] F. Biljecki, K. Kumar und C. Nagel, „CityGML Application Domain Extension (ADE): overview of developments,“ Open Geospatial Data, Software and Standards, 27 August 2018.

[4] J. Hütter, „KIT - IAI Homepage,“ 2018. [Online]. [Zugriff am 09 02 2020].

[5] PyQt, „PyQt Referencing Guide,“ 2012.



11:06 - 11:24

Interoperability between BIM and building energy modelling – a case study

Francesco Asdrubali1, Manuel Manzo2, Gianluca Grazieschi3

1University of Roma Tre, Italy; 2University of Roma Tre, Italy; 3University of Roma Tre, Italy

Aim and Approach

(max 200 words)

The paper aims to assess some interoperability issues between Building Energy Modelling (BIM) and dynamic Building Energy Modelling (BEM). The investigation is performed considering as a case study the design of a new residential complex composed of two terraced buildings located in the eastern belt of Rome. The two buildings are very similar and are designed following the most updated regulations about energy efficiency in Italy: they aim at the nearly zero energy standard. During their early design stage, the chosen case studies were modelled using Revit as a BIM platform. The BIM model was exported in Design Builder in order to perform a dynamic simulation of their energy consumptions in an optimization perspective.

Scientific Innovation and Relevance

(max 200 words)

Building Information Modelling is spreading in the recent years due to the legislations that impose it. Some energy simulation techniques have already been implemented in the BIM models since they can contain information about the thermo-physical properties of opaque and transparent surfaces. Moreover, some plug-ins can be added in BIM tools in order to perform energy analysis. However, in most cases, the energy modelling is simplified and stationary. In order to perform a dynamic energy simulation, it is appropriate to export the BIM model into a dynamic energy simulation software. This means that BIM and BEM tools should be interoperable. The interface between the two models still presents some limitations. Some research is needed to improve it and some potential software features for a better BIM to BEM interoperability are suggested.

Preliminary Results and Conclusions

(max 200 words)

The main difficulties and limitations in the interface between the two softwares are evaluated after the application to the case study. The creation of an accurate BIM-borne BEM model is quite time-consuming, laborious and subject to human made errors: the users are required to check the interoperability issues and, in some cases, to fix them manually.

After the description of the limitations found during the application, some suggestions are proposed in order to improve the interoperability between BIM and BEM models.

Main References

(max 200 words)

Léa Sattler, Samir Lamouri, Robert Pellerin, Thomas Maigne. Interoperability aims in Building Information Modeling exchanges: a literature review. IFAC-PapersOnLine, Volume 52, Issue 13, 2019, https://doi.org/10.1016/j.ifacol.2019.11.180.

Ehsan Kamel, Ali M. Memari. Review of BIM's application in energy simulation: Tools, issues, and solutions. Automation in Construction, Volume 97, 2019, Pages 164-180, https://doi.org/10.1016/j.autcon.2018.11.008.

Georgios Gourlis, Iva Kovacic, Building Information Modelling for analysis of energy efficient industrial buildings – A case study. Renewable and Sustainable Energy Reviews, Volume 68, Part 2, 2017, Pages 953-963, https://doi.org/10.1016/j.rser.2016.02.009.

Haily Fernald, Seungyeon Hong, Scott Bucking, William O’Brien. BIM to BEM translation workflows and their challenges: a case study using a detailed BIM model. Proceedings of eSim 2018, the 10ᵗʰ conference of IBPSA-Canada Montréal, QC, Canada, May 9-10, 2018.



11:24 - 11:42

Texture mapping and IFC material retrievement for virtual reality applications

Sebastian Duque Mahecha, Sergi Aguacil Moreno, Alexandre Dennis Stoll, Laurent Deschamps

Building2050 group, Ecole Polytechnique Fédérale de Lausanne (EPFL), Fribourg, Switzerland

Aim and Approach

(max 200 words)

Successful experiments have been carried out in order to enable interactive IoT device management through immersive environments supported by Virtual-Reality(VR) and Augmented Reality (AR)[1–7]. In these experiments, material texturing plays a key role in making the experience vivid and facilitating spatial orientation and object sight recognition. In parallel, Architecture, Engineering and Construction(AEC) professionals increasingly integrate into their practice Building Information Modelling(BIM) methodologies, notably relying on the IFC data model[8] as the open international standard [9,10]. According to these methodologies, digital models synthesising informed-3D elements function as central source of building data along the building lifecycle. In spite of the evident convenience of using such models for IoT device management, a review of current industry practice and scientific literature in achieving IFC-IoT integration shows that there is still a major difficulty in keeping together IFC parametric information and material textures. Therefore, this article analyses different workflows to manage IoT interactive environments capable of preserving, from the original model, the exported IFC geometric and parametric information, as well as the material-textures affected to the model's elements. More specifically, we describe an automated workflow IFC file > IFC verification definition correcting textures>Game Engine (Unity[11]), allowing the integration of material-textures to an IFC2.3 export.

Scientific Innovation and Relevance

(max 200 words)

To date, workflows available for immersive enabled IoT interactive environments allow retrieving either the material-texture information or the IFC parametric information. In general, using any game-engine software facilitates the transfer of texture information, but makes difficult retrieving the necessary IFC data to assure the IoT system connectivity. On the other hand, using IFC-compatible game-engine applications like Unity, which efficiently handle IFC data, pushes one to let go of texture information in spite the fact that, paradoxically, Unity's engine is particularly performant in terms of texture rendering. The reason for this, is that the current version IFC 4.2 does not suit a robust textures support, which may only be suited in the next major version, that is the IFC 5 [12]. In turn, most modelling software have hardly made it to IFC 2.3 certification [13]. Hence, stressing that under the circumstances it may take yet some years before modelling software providers can support texture information within an IFC based BIM methodology, this article describes an automated workflow to allow the updatable integration of material-textures into an IFC 2.3 export. In this way, it will be possible to work with material textures within a fully integrated BIM methodology.

Preliminary Results and Conclusions

(max 200 words)

Results of a first approach show that, after a relatively easy treatment in Blender+BlenderBIM [14,15], IFC parametric data can incorporate both material information and image-based texture definition. However, this procedure proved highly inefficient in relation to changes and updates in the original IFC exported-model. Thus, our second approach was to introduce our own script, in order to automate the procedure: a "transparent" step matching IFC entities and material-textures. Results are satisfactory in relation to the suppression and modification of elements. Currently we work on changes involving element addition. Reflecting on future applications it is important to highlight that textures, are more than a cosmetic artifice to produce impressive renderings. Being able to transfer material and texture information through workflows for different BIM usages is fundamental in achieving comprehensible immersive experiences, or getting results that are more precise in model-based simulations, such as light reflectance and solar irradiance studies. In the future, this method may as well indicate ways in which we will be able to exploit IFC's embedded material properties to retrieve physical material information as well as texture appearance from the model elements.

Main References

(max 200 words)

[1] G.White et al., Augmented reality in IoT, International Conference on Service-Oriented Computing. 11434,(2019)149–160.

[2] D.Jo, G.J.Kim, AR enabled IoT for a smart and interactive environment: A survey and future directions, Sensors 19,(2019).

[3] L.Müller et al., GuideMe: A mobile augmented reality system to display user manuals for home appliances, International Conference on Advances in Computer Entertainment Technology, 8253 (2013)152–167.

[4] K.M.Chang et al., An automated IoT visualization BIM platform for decision support in facilities management, Applied Sciences 8,(2018).

[5] SwissLivingChallenge, NeighborHub,(2017).

[6] S.Tang et al., Automation in Construction A review of building information modeling (BIM) and the internet of things ( IoT ) devices integration: Present status and future trends, Autom. Constr. 101 (2019)127–139.

[7] B.Dalton, M.Parfitt, Immersive Visualization of Building Information Models, Design Innovation Research Centre working paper 6(2013)1–20.

[8] BuildingSMART, Industry Foundation Classes-IFC,(2020).

[9] M.Poljanšek, Building Information Modelling (BIM) standardization,(2017).

[10] A.Kiviniemi et al., Review of the Development and Implementation of IFC compatible BIM Executive Summary, ERA Build(2008)1–2.

[11] UnityTechnologies, Unity platform,(2005). https://unity.com/.

[12] J.Ouellette, IFC-Problem about Elements with Texture, BuildingSMART forum, (2019). https://forums.buildingsmart.org/.

[13] BuildingSMART, IFC certified software,(2020). https://www.buildingsmart.org/.

[14] R.Ton, Blender Foundation,(2018).

[15] BlenderOrg, BlenderBIM - IfcOpenShell software library,(2019). https://blenderbim.org/.



11:42 - 12:00

Proposed integration of utilities in the Energy ADE 2.0

Maximilian Schildt, Christian Behm, Avichal Malhotra, Sebastian Weck-Ponten, Jérôme Frisch, Christoph van Treeck

Institute of Energy Efficiency and Sustainable Building (E3D), RWTH Aachen University, Germany

Aim and Approach

(max 200 words)

Energy Performance Simulations often require a large amount of data for building and district level simulations. This data highly depends on the quality, quantity as well as granularity of individual models and parameters. However, for efficiently storing, exchanging and reusing the information, a comprehensive data management system is very important. The management system should contain the relevant data from a district level to individual buildings in terms of geometry, HVAC components as well as network information in order to run energy performance simulations and operation optimization. Database management systems, such as 3D CityDB [1], do allow the storage of semantic data for 3D CityGML [2] building and virtual city models. Furthermore, for structuring the energy specific data, the use of the CityGML Energy Application Domain Extension [3] is foreseen. Currently, a comprehensive structuring of the energy systems data is missing in the Energy ADE 2.0 and therefore, the aim of this paper is to propose an approach to fill the gap for the management system. Moreover, the access to specific HVAC components within the data structure facilitates not only the analysis of energy demands but also the selection of components to cover the demand in a cost- or CO2-efficient manner.

Scientific Innovation and Relevance

(max 200 words)

Based on the investigations over the energy systems within a field test of a collaborative research project, a perspective blueprint for the decentralized energy system transformation is developed. Furthermore, within the scope of this paper, a decisive analysis will be carried out to determine the components of plant and building technologies that should be additionally mapped with its respective degrees of detail and their individual key performance indicators. The components to be mapped will be systematically structured and classified based on the Energy ADE schema into related categories such as energy sources, conversion and transmission. This paper will show an in-depth analysis to determine the coherence of the components that can be mapped using the existing ADEs [4]. For the missing components, however, a modular XML schema definition (XSD) will be developed based on the central dependencies between the established categories. This approach allows the simulations of CO2-emissions and footprints in districts that are linked to a central database. Moreover, this will serve as a basis for optimized choice, dimensioning and operation of energy systems and utilities at an urban scale.

Preliminary Results and Conclusions

(max 200 words)

Presently, the XML schema of Energy ADE has been extended using the classes necessary to map energy systems and utilities on district and building levels. The template of the extended classes has been linked to the 3DCityDB schema in an object-oriented database for implementation of the aforementioned research project. The approach is to attain a database that takes the utilities and energy systems fully into account and furthermore enables a tool-chain for energetic simulations and optimization scenarios. Comparing to Industry Foundation Classes (IFC) [5], CityGML and Energy ADE allow reduced order modelling and thereby reduce the amount of data needed to feed large datasets of buildings and districts into a simulation and optimization tool-chains. The current usage of CityGML Energy ADE and 3DCityDB is being investigated with the vision of reducing data redundancy while saving multi-criteria simulation results and optimization scenarios.

Main References

(max 200 words)

[1] Z. Yao, C. Nagel, F. Kunde, G. Hudra, P. Willkomm, A. Donaubauer, T. Adolphi and T. H. Kolbe, "3DCityDB – a 3D geodatabase solution for the management, analysis, and visualization of semantic 3D city models based on CityGML," Open Geospatial Data, Software and Standards, 2018.

[2] G. Gröger, T. Kolbe, C. Nagel and K. Häfele, "OGC City Geography Markup Language (CityGML) Encoding Standard," OGC, 2012.

[3] G. Agugiaro, J. Benner, P. Cipriano and R. Nouvel, "The Energy Application Domain Extension for CityGML: enhancing interoperability for urban energy simulations," Open Geospatial Data, Software and Standards, 5 March 2018.

[4] F. Biljecki, K. Kumar and C. Nagel, "CityGML Application Domain Extension (ADE): overview of developments," Open Geospatial Data, Software and Standards, 27 August 2018.

[5] buildingSMART, "IFC Specifications Database," 18 06 2020. [Online]. Available: https://technical.buildingsmart.org/standards/ifc/ifc-schema-specifications/. [Accessed 06 07 2020].

 
12:00 - 13:00Lunch
Location: Foyers (Concert Hall) and 'het Zand' square outside (front of building)
Foyers (Concert Hall) and 'het Zand' square outside (front of building) 
12:00 - 13:00MB1: Meet the Board - General information: What is IBPSA, what is the purpose, our books, newsletter & projects etc
 
12:00 - 13:00MB2: Meet the Board - Become a member of the organisation (information on affiliates, memberships and sponsoring)
 
12:00 - 13:00MB3: Meet the Board - How do I get involved? Join a committee (information on the work we are doing in the different committee and how people could contribute
 
13:00 - 14:30Session W2.1: Practice and industry related case studies
Location: Concert Hall - Forum 6
Session Chair: Dorota Brzezińska, Lodz University of Technology
Session Chair: Friedl Decock, Daidalos Peutz bouwfysisch ingenieursbureau
Concert Hall - Forum 6 
 
13:00 - 13:18

Simulation support for the design of ventilated windows: a case study

Shiva Najaf Khosravi, Ardeshir Mahdavi

Vienna University of Technology, Austria

Aim and Approach

(max 200 words)

Efforts to develop advance building envelope components include, among other things, ventilated window constructions. These windows utilize the airflow between glazing panes to preheat outside air before it enters indoors. In the framework of a previous research project, an instance of such a system was implemented in a testbed and was subjected to experimental studies under real conditions. This system comprises a single glazing unit as the outer pane and double glazing as the inner wing. The thermal behavior of the system and its capacity to preheat ventilation air was investigated. In the present contribution, we report on high-resolution 3D steady-state CFD simulation of this component. Model results were compared with measurements. The aim was to explore the fidelity of the CFD model and its potential toward design support. Specifically, variables related to the size of the outlet opening as well as the position of double glazing were examined under.

Scientific Innovation and Relevance

(max 200 words)

In the last few decades, the thermal behavior of ventilated windows, or supply air windows, has received much attention in the literature [1-5]. This type of window, which can be deployed in both new and old buildings, is meant to provide in the cold season preheated ventilated air [6,7]. Nevertheless, predicting the thermal performance of a ventilated window is not a trivial task. Temperature and airflow patterns emerge from numerous dynamic interrelated thermal processes. These processes depend on the geometry and thermophysical properties of ventilated window components, building itself, and weather conditions [2, 5, 7]. The present research aimed to characterize a ventilated window in terms of its flow field (velocity and temperature distribution) while considering the influence of solar energy transmittance on temperature and airflow fields. This was done by numerically modeling the fluid dynamic and heat transfer in a ventilated window and solving the model in a CFD code. Furthermore, the experimental measurement data was applied to evaluate the reliability of the CFD model.

Preliminary Results and Conclusions

(max 200 words)

The CFD model utility was demonstrated in terms of the design optimization of the supply air (ventilated) window. Specifically, we documented the thermal behavior of the ventilated window and evaluated the risk of condensation. A numerical model was created with a CFD commercial software in order to simulate the working of the ventilation outlets vents and the glazing unit’s performance. The CFD investigation indicates that ventilated windows can provide preheated fresh air to the buildings’ interior spaces. Simulation results suggest, in this case, that smaller inlet opening dimensions may be conducive to obtaining better performance regarding the temperature and volume flow of the incoming air. Furthermore, the application of double-layered glazing on the outside wing can lower the condensation risk during the cold season.

Main References

(max 200 words)

1. Gosselin, J.R. and Q. Chen, A computational method for calculating heat transfer and airflow through a dual-airflow window. Energy and Buildings, 2008. 40(4): p. 452-458.

2. Bhamjee, M., A. Nurick, and D.M. Madyira, An experimentally validated mathematical and CFD model of a supply air window: Forced and natural flow. Energy and Buildings, 2013. 57: p. 289-301.

3. Carlos, J.S., Real climate experimental study of two double window systems with preheating of ventilation air. Energy and Buildings, 2010. 42(6): p. 928-934.

4. McEvoy, M.E., R.G. Southall, and P.H. Baker, Test cell evaluation of supply air windows to characterise their optimum performance and its verification by the use of modelling techniques. Energy and Buildings, 2003. 35(10): p. 1009-1020.

5. Laverge, J., Condensation in a closed cavity double skin facade: a model for risk assessment. 2010.

6. Hasse, M. and T. Wigenstad, Condensation Issues in Ventilated Façades, in Materials with Complex Behaviour II. Advanced Structured Materials, A. Öchsner, L.F.M.d. Silva, and H. Altenbach, Editors. 2012, Springer: Berlin.

7. Tanimoto, J. and K. i. Kimura, Simulation study on an air flow window system with an integrated roll screen. Energy and Buildings, 1997. 26(3): p. 317-325.



13:18 - 13:36

Daylighting simulation using spectral ray tracing

Antony Escudie1, Chloé Therreau1, Tanguy Timmermans2, Louis Dellieu2, Grégoire Besse1

1Eclat Digital; 2AGC Glass Europe

Aim and Approach

(max 200 words)

Direct sunlight is poor for visual comfort in offices or homes. Areas exposed to direct sunlight are too bright, with illuminances over 10000 lx, making most computer displays unreadable. The contrast between lit zones and dark zones is generally too high, requiring the eye to constantly adapt when looking at different places of the same room : this can be an important cause of eye fatigue.

People will generally react by closing the curtains or masking the sun light by any other mean. Then, the indoor lighting will be too low for comfortable work, and they will switch on artificial lights.

Day-lighting in bright sunlight is a main concern in architecture : using special designs and materials, it is possible to improve significantly the visual comfort. These techniques can be realistically simulated with Ocean, spectral ray tracing software.

Scientific Innovation and Relevance

(max 200 words)

Unlike traditional building light simulation software, no model simplification is necessary : it may work with fully detailed CAD models and several millions of polygons. The same software and model may be used for producing detailed illuminance mappings, as well as realistic renderings for visualization.

Preliminary Results and Conclusions

(max 200 words)

In this simple day-lighting example, we demonstrated the broad possibilities of the Ocean software for lighting design. The exact nature of its calculations allow making quantitative analysis of day-lighting performance. As it is possible to work on detailed CAD models, with complex materials based on measured spectral data, testing virtually any day-lighting system design is possible.

Main References

(max 200 words)

Physically Based Rendering : from theory to implementation, M. Pharr et. al, Third Edition, (2004)

Robust Monte Carlo Methods for Light Transport Simulation, E. Veach. Stanford University, (1997)



13:36 - 13:54

Evaluating daylighting performance metrics in LEED v4 for commercial office buildings: What criteria is missing to enhance the visual performance and comfort of occupants?

Riwayat Katia, Nourhan Elsayed, Tarek Rakha

Georgia Institute of Technology, United States of America

Aim and Approach

(max 200 words)

The Leadership in Energy and Environmental Design (LEED) is one of the most widely adopted building benchmarks globally, and it encompasses multiple rating criteria for performance. However, such criteria typically focus on reducing energy consumption, and may disregard providing a high-level of occupant satisfaction. Recently, LEED has adopted grid-level Climate-based Daylighting Metrics (CBDM) as one of the possible metrics for daylighting evaluation. This approach focuses on a desk height evaluation of Spatial Daylighting Autonomy (sDA) and Annual Solar Exposure (ASE), which may disregard an occupant’s visual comfort at eye level. This paper proposes a more comprehensive approach to daylighting performance evaluation in commercial office space that incorporates vertical-eye level glare evaluation, in addition to desk-level CBDM. Simulations for workspaces in a tall office building in Atlanta, GA, USA at varying orientations and proportions were undergone using Climate Studio. Simulations were conducted with different shading systems to maximize sDA and minimize ASE and Annual Glare. The simulations followed the same thresholds for sDA and ASE as proposed by LEED. However, thresholds for annual glare were set based on proposed recommendations in the literature which were; Likely to be comfortable: DGP<0.23, Bounded between comfort and discomfort: 0.23<DGP<0.25, Likely to be uncomfortable: DGP>0.25.

Scientific Innovation and Relevance

(max 200 words)

Overlooking occupants' dynamic behaviours and reducing their needs to a set of limited parameters required by standards (e.g., illuminance thresholds) can cause a decline in satisfaction and consequent energy inefficiency in LEED buildings. The LEED program adopted the use of sDA and ASE to predict daylight sufficiency and probability of glare respectively, (IES LM-83-12, 2012) as one of the three compliance paths for acquiring the ‘Daylight & Views’ credits in LEED v4 (LEED Reference Guide, 2014). However, LEED did not consider that LM-83-12 also stated that there are other sources of glare besides direct sunlight that are not fully evaluated by the ASE metric. ASE evaluates disability glare when the amount of light is excessive and the occupant can’t see, but does not evaluate discomfort glare at the eye level, when there is a range of luminance in a field of vision that causes degradation of visual performance and tiring of the eyes (Carlucci et al., 2015), thus, reducing the level of occupants’ satisfaction significantly. This paper’s innovation is in proposing a comprehensive approach that includes the addition of Annual Glare evaluations as a metric, with the tested thresholds as the criteria for obtaining the LEED credits.

Preliminary Results and Conclusions

(max 200 words)

Three sidelit private offices in the north, west, and south orientations along with two sidelit open plan offices in the north and east orientations on the 16th floor of 191 Peachtree Tower, Atlanta, GA were investigated. When an overhang and horizontal louvers were placed at 0 degrees in the sidelit private offices in the west and south orientations, the offices acquired all four LEED credits (100% sDA, 0.0% ASE). However, they suffered from 48.4% and 14.8% of disturbing glare percentages respectively, (0.40<DGP<0.45) over the year for more than 5% of time. When the same horizontal louvers were tilted at 45 degrees, the annual glare was reduced to 1.6% and 1.7% respectively, with the same values for sDA and ASE. Similarly, when horizontal louvers tilted at 45 degrees were placed with the overhang in the open plan office in the east orientation, the annual glare was reduced from 21.3% to 0.0% with the ASE at 0.0% in both cases. These preliminary results justify further in-depth investigation at different orientations with other shading configurations to evaluate annual glare based on a new recommended threshold. This can guide LEED and other benchmarks to require more stringent and comprehensive daylighting performance metrics.

Main References

(max 200 words)

Carlucci et al. (2015). A review of indices for assessing visual comfort with a view to their use in optimization processes to support building integrated design. Renewable and Sustainable Energy Reviews 47, 1016-1033.

IES LM-83-12. (2012). Retrieved April 10, 2017.

Jakubiec, J. A., & Reinhart, C. F. (2012). The 'adaptive zone'- A concept for assessing discomfort glare throughout daylit spaces. Lighting Research and Technology, 44(2), 149–170.

LEED v4 BD+C Reference Guide. (2014). Retrieved April 10, 2017, from U.S. Green Building Council.

Solemma. (2020). Climate Studio. Retrieved March 19, 2020.

Van Den Wymelenberg, K., Inanici, M., & Johnson, P. (2010). The effect of luminance distribution patterns on occupant preference in a daylit office environment. LEUKOS - Journal of Illuminating Engineering Society of North America, 7(2), 103–122.

Van Den Wymelenberg, K., & Inanici, M. (2014). A critical investigation of common lighting design metrics for predicting human visual comfort in offices with daylight. LEUKOS - Journal of Illuminating Engineering Society of North America.

Wilder, R., Mukhopadhyay, J., Femrite, T., & Amende, K. (2019). Evaluating glare in leed certified buildings to inform criteria for daylighting credits. Journal of Green Building, 14(4), 57–76.



13:54 - 14:12

Designing a Solar Shading Solution parametrically using the direct sun and the view to the outside for a building in Vietnam

Pedro Marques, Chinh Trieu, Wim Boydens

Studiebureau Boydens, Belgium

Aim and Approach

(max 200 words)

In hot and humid climates where the sun is a permanent cooling load, façade optimization can be performed deeply with the aid of radiance-based daylight simulations. However, during design phase of a project, the extent of the parametric analysis is generally time-restricted.

For a mixed-use building in Vietnam, a grasshopper script was set up in order to aid the design team in optimizing the depth, width and density of vertical fins on the outer façade. The first instinct was the use of daylight simulations, so that the second skin would allow just the right amount of daylight in - too much leads to glare and overheating, not enough leads to artificial lighting usage.

After the first attempts, the initial setup was unsatisfactory. Simulations were taking too long, and the best results were produced by a densely populated outer facade, where the view to the outside was fractional.

Given the need to answer the time and design constraint of the project, a new approach was developed, using two factors - direct sun penetration and view to the outside. By turning the exercise into a static calculation, one was able to calculate thousands of possibilities for each element of the outer facade.

Scientific Innovation and Relevance

(max 200 words)

The use of static calculations in parametric evaluations can reduce by 50 the amount of time necessarily to run façade studies parametrically. This would mean that, while a radiance-based study can study 100 variations, a static approach could reach 5000. Furthermore, radiance-based simulations are not responsive enough to be used in design team meetings, whereas a static approach is extremely helpful.

From the variety of the final results, the cherry-picked results could be secondly checked more thoroughly through the use of radiance-based simulations.

Preliminary Results and Conclusions

(max 200 words)

The creation of an alternative path to optimization lead to a timely evaluation of the building facade, which worked effectively within the feedback loop of the design team. Thanks to the speedy and personalized approach, the design team changed its design for a better performing second skin.

Main References

(max 200 words)

nothing to declare



14:12 - 14:30

Facades, roofs and solar parking yield estimation at Utrecht science park

Tayzer Damasceno de Oliveira1,2,3, Luis Fialho2, Atse Louwen3,4, Wilfried G.J.H.M. van Sark3

1Accenture, Lisboa, Portugal; 2University of Évora, Évora, Portugal; 3Utrecht University, Utrecht, The Netherlands; 4Eurac Research, Bolzano, Italy

Aim and Approach

(max 200 words)

The goal of this work is to estimate the yearly potential and estimate the number of Electric vehicles charged per day using solar photovoltaic cells at Utrecht Science Park, located at Utrecht, The Netherlands. The first part is related to use ArcGIS to build the building shapefile with the building's height. The second use starts using the AutoCAD to apply the extrusion to make the building in 3D, Revit with the use of solar analysis tool that helps to find the best places to install the PV system. The third part belongs to the calculus to estimate how many charging stations we can have using the solar parking lots. Three layouts (VC0 [traditional], VC1, and VC2) were used in order to compare the yearly potential. The VC0 (16 767 kW) has the solar panels only on the roofs turned south. VC1 (26 769 kW) has the layout designed for the solar panels on the roofs and solar parking turned to the south direction, and VC2 (37 893 kW) with the cells turned to the east-west direction. And the facades turned south.

Scientific Innovation and Relevance

(max 200 words)

The innovation relates to the attachment of the solar panels inside a building that is already in use, instead of the change the structure to integrate them. The solar parking lot has a great benefit using the parking lots to produce energy and protecting the cars from the weather conditions like hail, snow and etc. In addition, the use of this technology help to make the building a Nearly zero-energy building using the energy inside the building. Simultaneously using the charging station where the employees and students can charge their EV or even some electronic devices. Furthermore, demonstrating to the students the importance of using renewable energies (solar energy on this project) and how it works.

Preliminary Results and Conclusions

(max 200 words)

The VC0 has a production of 13 549 MWh/year, VC1 with 19 708 MWh/year, and VC2 of 24 083 MWh/year, having the performance ratio of 0.71, 0.70, and 0.65. On the side of economic analysis, the NPV is positive for all of them, the Payback has the lowest value for VC0 that is 5.54, VC1 has 6.53, and VC1 with 8.02. The IRR is 14.06% for VC0, 11.83% for VC1, and 9.27% for VC2. The LCOE has the lowest value for VC0, being 0.068 €/kWh for VC0, 0,078 €/kWh for VC1, and 0.093 for VC2. Generally looking, VC0 represents the best option, especially if we take into consideration the economical results, but in the side of innovation, VC1 goes further because the parameters are better than VC2, and for this work, we didn't count the economic returns with the charging of the EV.

Main References

(max 200 words)

AHN, Actueel Hoogtebestand Nederland (actual height data of the Netherlands), www.ahn.nl (2021).

Fouad MM, Shihata LA, Mohamed AH. Modeling and analysis of Building Attached Photovoltaic Integrated Shading Systems (BAPVIS) aiming for zero energy buildings in hot regions. Journal of Building Engineering, 21, 18-27, 2019.

Eldin, A. H., Refaey, M., & Farghly, A. (2015). A Review on Photovoltaic Solar Energy Technology and its Efficiency.

Jacobson, M. Z., & Jadhav, V. (2018). World estimates of PV optimal tilt angles and ratios ofsunlight incident upon tilted and tracked PV panels relative to horizontal panels. Solar Energy, 169, 55-66.

Oliveira, T. D. (2020). Facades and solar parking yield estimation at Ultrecht University (Master's thesis, Universidade de Évora).

Reich, N.H., Mueller, B. Armbruster, A., Van Sark, W.G.J.H.M., Kiefer, K., & Reise, Ch. (2012). Performance Ratio revisited: are PR > 90% realistic?. Progress in Photovoltaics, 20, 717-726

 
13:00 - 14:30Session W2.2: Ensuring high quality building simulations
Location: Concert Hall - Artiestenfoyer
Session Chair: Laura Carnieletto, University of Padova
Session Chair: Frederik Maertens, boydens engineering
Concert Hall - Artiestenfoyer 
 
13:00 - 13:18

Heat and moisture transport through a living wall system designated for greywater treatment

Hayder Alsaad, Conrad Voelker

Bauhaus-University Weimar, Germany

Aim and Approach

(max 200 words)

Façade greening systems designated for remediating greywater can help to relieve the water treatment centres while saving on irrigation water (Prodanovic et al. 2017). This study aims to numerically investigate the heat and moisture transport in such systems. As most heat and moisture simulation models cannot simulate the complex impact of vegetation on the simulated parameters, this study was conducted by coupling two simulation tools: ENVI-Met and Delphin. ENVI-Met is a high-resolution meteorological model that can simulate the interaction between urban geometry, vegetation, and the outdoor environment (Bruse and Fleer 1998). Delphin, on the other hand, is a simulation package for coupled heat and moisture transport in porous building materials (Grunewald 2000). In the present study, ENVI-Met was used to calculate the influence of the plants on air temperature, velocity, relative humidity, wind direction, and radiation (long wave and short wave) on the façade. Subsequently, the calculated parameters were then imposed on the façade in Delphin. Thus, ENVI-Met was used to determine the local climate conditions on the façade, which were used to conduct the hygrothermal simulations with Delphin. The hygrothermal simulations had a duration of four years to reach the equilibrium moisture content in the construction.

Scientific Innovation and Relevance

(max 200 words)

With the continuously increasing levels of pollution in cities and rising temperatures due to the urban heat islands, living walls have been growingly investigated because of their promising potential in improving the urban environment. In addition, these systems can have a significant impact on the performance of the walls on which they are mounted. The literature indicates that façade greening can improve the heating demand of the building (Tudiwer and Korjenic 2017). Yet, due to evaporation from the substrate and transpiration from the plants, the relative humidity on the façade can increase (Capener and Sikander 2015). Moreover, as the greening system investigated in this study is meant for greywater treatment, it involves continuous water flow in the substrate of up to 50-75 L/d. An increase in humidity can damage the building material and reduce the energy efficiency of the building by increasing the heat conductivity of the wall layers. As hygrothermal simulations of living walls designated for greywater treatment is not reported in the literature, this study aims to investigate the impact of relatively high exposure to moisture on façades.

Preliminary Results and Conclusions

(max 200 words)

To evaluate the impact of the living wall, two simulation models were created: a façade covered with a living wall and a reference facade with no greening. Both facades had a generic brick structure with a total thickness of 420 mm. The simulations showed that while the living wall was emitting water vapour, it did not increase the humidity content in the structure because of the ventilated air gap between the greening and the façade. In fact, the facade greening protected the wall from wind-driven rain and thus had a 16% less humidity content in the fourth simulation year in comparison to the reference case. The relative humidity of the interior surface of the wall was almost similar in both cases (58.3% with greening and 59.8% without greening). In the summer months (21 June – 21 September), the living wall cooled the façade's surface temperature due to shading, the thermal mass of the substrate, and the passive cooling of the plants. The maximum surface temperature behind the greening was 25°C compared to 40.6°C without greening. In the winter, the greening increased the minimum interior surface temperature by 1.2 K, which indicates an improvement in the thermal resistance of the construction.

Main References

(max 200 words)

Bruse, Michael; Fleer, Heribert (1998): Simulating surface–plant–air interactions inside urban environments with a three dimensional numerical model. In Environmental Modelling & Software 13 (3-4), pp. 373–384. DOI: 10.1016/S1364-8152(98)00042-5.

Capener, Carl-Magnus; Sikander, Eva (2015): Green Building Envelopes – Moisture Safety in Ventilated Light-weight Building Envelopes. In Energy Procedia 78, pp. 3458–3464. DOI: 10.1016/j.egypro.2015.11.179.

Grunewald, John (2000): Documentation of the Numerical Simulation Program DIM3.1", Volume 2: User's Guide. Insitute of Building Climatology, Faculty of Architecture, Univesity of Technology Dresden.

Prodanovic, Veljko; Hatt, Belinda; McCarthy, David; Zhang, Kefeng; Deletic, Ana (2017): Green walls for greywater reuse. Understanding the role of media on pollutant removal. In Ecological Engineering 102, pp. 625–635. DOI: 10.1016/j.ecoleng.2017.02.045.

Tudiwer, David; Korjenic, Azra (2017): The effect of living wall systems on the thermal resistance of the façade. In Energy and Buildings 135, pp. 10–19. DOI: 10.1016/j.enbuild.2016.11.023.



13:18 - 13:36

A convolutional neural network for the hygrothermal assessment of timber frame walls

Astrid Tijskens, Staf Roels

KU Leuven, Belgium

Aim and Approach

(max 200 words)

Timber frame walls typically consist of a wind barrier at the cold exterior side and a vapour barrier at the warm interior side. In cold climates, the vapour barrier must have a higher vapour resistance than the wind barrier, to ensure vapour that entered the construction at the inside can dry out towards outside. However, there are no general guidelines available as to which combinations of wind and vapour barrier are safe in a specific context. Sometimes, a rule of thumb is used, which requires the ratio between the vapour resistances of vapour and wind barrier to be between 5 and 15 or even higher. This rule, however, does not take into account moisture buffering capacity of the structure nor specific climatic aspects, and hence does not guarantee an optimal solution. Because a hygrothermal simulation for every case would be too time-intensive, a metamodel is proposed in the current study, which allows quickly determining adequate combinations of wind and vapour barrier under given conditions. A convolutional neural network for time series is used to replace the hygrothermal simulations, thus allowing flexibility in the desired post-processing.

Scientific Innovation and Relevance

(max 200 words)

The use of neural networks for time series predictions is a fairly novel metamodelling strategy in the field of building physics. When evaluating the hygrothermal performance of a building component in a probabilistic framework, metamodelling strategies have in the past been applied to predict specific and single-valued performance indicators. This approach provides little flexibility and might not provide sufficient information for decision-making. Instead, a metamodel predicting hygrothermal time series, as calculated by the original hygrothermal model, provides more information and allows the user to post-process the output as desired. In [1-2], the authors proved the applicability of convolutional neural networks for hygrothermal calculations of massive brick walls. The current study explores the models to predict the hygrothermal response of timber frame walls.

Preliminary Results and Conclusions

(max 200 words)

First results show that it is possible to replace the time-consuming hygrothermal model with a much faster convolutional neural network, while maintaining high accuracy. Since material properties, such as (humidity dependent) vapour resistance and moisture buffering capacity, play a significant role in the hygrothermal response, the network requires additional input on this, compared to the network from [1-2], resulting in a slightly different network architecture.

Main References

(max 200 words)

[1] A. Tijskens, S. Roels, and H. Janssen, “Neural networks for metamodelling the hygrothermal behaviour of building components,” Building and Environment, vol. 162, no. June, p. 106282, 2019.

[2] A. Tijskens, H. Janssen, and S. Roels, “Optimising Convolutional Neural Networks to Predict the Hygrothermal Performance of Building Components,” Energies, vol. 12, no. 20, p. 3966, 2019.



13:36 - 13:54

Besos: a python library that links energyplus with energy hub, optimization and machine learning tools.

Theodor Victor Christiaanse1,2, Paul Westermann1,2, Will Beckett1,2, Gaelle Faure1,2, Ralph Evins1,2

1Energy in Cities group, Department of Civil Engineering, University of Victoria, BritishColumbia, Canada; 2Institute for Integrated Energy Systems, University of Victoria, British Columbia, Canada

Aim and Approach

(max 200 words)

The goal of the BESOS library is to create an easy way for academics start building modelling experiments that involve linking EnergyPlus with optimization, energy system design and machine learning techniques. The Building and Energy Simulation, Optimization and Surrogate-modelling (besos) library provides a Python-based software bridge between EnergyPlus and various other environments. Furthermore, software abstractions are specifically setup such that building energy modellers can quickly create numerous model variations using parametric definitions. These include optimizing the building design and energy systems, and integration of the modeling results with machine learning techniques. Accompanying the Python library, a web platform (BESOS) [1] is freely accessible for academics to use the software, learning through our extensive library of examples and developing new software extensions on top of the existing software paradigms.

Scientific Innovation and Relevance

(max 200 words)

The optimal exploration of building design and operation requires the use of many software tools. Among them, EnergyPlus (E+) is a commonly used physics-based building energy simulation tool. The use of machine learning (ML) is finding adoption among engineers in the field and may have a huge impact on the speed and breath of modelling experiments. ML techniques can perform different tasks that could inform building design and operation such as; (i) capture the dynamics of a physics-based models in a fast and accurate surrogate model [2] reducing the cost of expensive exploration, (ii) large building datasets of E+ or real timeseries data can be analysis on a building-by-building level using ML techniques [3], (iii) retrofit measures may be identified by understanding the timeseries sensor data through black box techniques [4], (iv) forecasting future energy performance of the building stock using ML for forecasting [5].

The potential of these techniques ML techniques is evident. The integration between these new Python-based libraries and physics-based modelling tools used for energy modelling was limited. Our software library gives modellers the ability to create building models that work in E+ and manipulate the inputs and outputs of the E+ model within a Python environment.

Preliminary Results and Conclusions

(max 200 words)

The Python environment allows for the integration with these new novel machine learning libraries such as TensorFlow and Scikit-learn. Furthermore, we have also included links to powerful optimization solvers and energy system design tool Energy Hub. These three tools provide numerous options for energy modelers to combine multivariant data sets and E+ models to create experiments that stack many different techniques into a single interface.

We will discuss the challenges and successes we have had building the software library besos and BESOS platform. A demo of the software capabilities will be shown and demonstration how multi-model ecologies can be built are presented. A list of recent projects and papers that are would not be possible without the platform [2-5]. Finally, we will share how we continue to improve the underlying software for the next possible versions by partnering with computer scientists and making innovative technologies available to the building modelling domain.

Main References

(max 200 words)

[1] Faure G, Christiaanse T, Evins R, Baasch GM. BESOS: a Collaborative Building and Energy Simulation Platform. In Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation 2019 Nov 13 (pp. 350-351).

[2] Westermann P, Evins R. Surrogate modelling for sustainable building design–A review. Energy and Buildings. 2019 Sep 1;198:170-86.

[3] Baasch G, Wicikowski A, Faure G, Evins R. Comparing gray box methods to derive building properties from smart thermostat data. In Proceedings of the 6th ACM international conference on systems for energy-efficient buildings, cities, and transportation 2019 Nov 13 (pp. 223-232).

[4] Westermann P, Deb C, Schlueter A, Evins R. Unsupervised learning of energy signatures to identify the heating system and building type using smart meter data. Applied Energy. 2020 Apr 15;264:114715.

[5] Westermann P, Braun J, Murphy E, Grieco J, Evins R. Insight Into Predictive Models: On The Joint Use Of Clustering And Classification By Association (CBA) On Building Time Series. In Rome, Italy; [cited 2020 Jul 16]. p. 1564–71. Available from: http://www.ibpsa.org/proceedings/BS2019/BS2019_211236.pdf



13:54 - 14:12

Data-driven black box model of building dynamics

Sophie Bernard1,2, Valery Ann Jacobs1, Bert Belmans1,3, Arjen Mentens1, Filip Descamps1,4, John Lataire1

1Vrije Universiteit Brussel, Belgium; 2Université libre de Bruxelles, Belgium; 3Universiteit Antwerpen, Belgium; 4Daidalos Peutz, Belgium

Aim and Approach

(max 200 words)

In this research a modelling tool is presented to derive surrogate models of thermal energy transfers in buildings, to support the development and testing of smart control algorithms.

A data-driven approach was used to identify a model able to predict the indoor temperature in a case-study building when an electric heater was turned on. The data about the system was generated by EnergyPlus simulations, which resolve the heat balance equations to simulate the thermal response of a building. The model structure that was selected is a second-order ARMAX transfer function whose parameters were identified with a Least Squares optimization criterion. The model inputs were limited to the heater’s power, the global horizontal solar radiation and the outdoor dry-bulb temperature.

Scientific Innovation and Relevance

(max 200 words)

Buildings account for one-third of the global energy consumption in the world, which is more than the industry sector or the transport sector. For environmental and economic reasons, it is thus important to reduce their energy consumption, while preserving a comfortable environment for their occupants. In this context, computer-aided control techniques for building comfort systems can be a valuable asset. Advanced control techniques, such as model predictive control, require supporting system models for development and testing. However, detailed physical models that carefully take system dynamics into account are too computationally intensive for practical applications. This is why surrogate models of low complexity are highly relevant.

The innovative element is that a frequency domain modelling approach is used. This allows to conveniently select the frequency band of interest. Namely, the dynamics are mostly important at low frequencies. Discarding the high frequencies implicitly removes a significant amount of noise.

Also, the use of a data-driven approach implicitly takes into account influences which, in a first principles approach, might have been neglected. That is, the model is validated on the data rather than on physical insight.

Preliminary Results and Conclusions

(max 200 words)

Simulation experiments have been conducted where random binary sequences (a sequence of step inputs) have been applied as the heater's input, and historical weather conditions have been used for the solar radiation and the outside air temperature.

A transfer function model was obtained, describing the relation between the inputs (heater and weather conditions) and the resulting ambient temperature in the room. A data set corresponding to the month of July was used for the identification, and the resulting model was then validated on a data set of the month of December.

It was demonstrated that the model was able to predict fairly accurately the indoor temperature when the building was subject to winter or summer weather conditions. Further improvements and refinements will be carried out, including taking into account the difference in time constants of the heater and the weather conditions.

Main References

(max 200 words)

P. Abrahams et al., Method for Building Model Calibration to Assess Overheating Risk in a Passive House in Summer, Proceedings of the 16th IBPSA conference, Rome, Italy, Sept. 2-4, 2019, DOI 10.26868/25222708.2019.210768

S. Mostafavi et al., Model Development for Robust Optimal Control of Building HVAC, Proceedings of the 16th IBPSA conference, Rome, Italy, Sept. 2-4, 2019, DOI 10.26868/25222708.2019.211331

S. Royer, Energy and Buildings, Volume 78, pg. 231-237, A procedure for modeling buildings and their thermal zones using co-simulation and system identification, 2014. DOI 10.1016/j.enbuild.2014.04.013

S. Royer et al., IFAC Proceedings Volumes, Volume 47, Issue 3, Pages 10850-10855, Black-box modeling of buildings thermal behavior using system identification, 2014. DOI 10.3182/20140824-6-ZA-1003.01519

R. Pintelon and J. Schoukens. System Identification: A Frequency Domain Approach. John Wiley, 2nd edition, 2012.



14:12 - 14:30

Summer passive strategies assessment based on calibrated building model using on site measurement data

Obaidullah Yaqubi1,2,3, Auline Rodler1,2, Sihem Guernouti1,2,3, Marjorie Musy1,2,3

1Equipe de recherche BPE, Cerma Ouest, Nantes, France; 2Institut de Recherche en Sciences et Techniques de la Ville (IRSTV) , Nantes, France; 3CNRS UMR 6183, GeM, Université de Nantes, France

Aim and Approach

(max 200 words)

With the changes in worldwide climate conditions, extreme summer heat events will become more frequent and severe rendering buildings uncomfortable. This paper in this context, presents the application of co-simulation on practical design issues of mixed mode ventilated buildings. It is based on a 2-months field study measurement of outdoor and indoor air temperatures and window operation of an existing residential building during the hottest season of the year in Nantes (France) in 2018.

The aim of this study is first to use measured indoor temperature to calibrate a building co-simulation model and second to evaluate how openness ratio of windows and operation of window shutters affect the indoor thermal comfort during summer.

Scientific Innovation and Relevance

(max 200 words)

Two modelling tools, Contam and Trnsys, were coupled to simultaneously simulate airflow and temperature dynamics of the whole building. Since each of the five storeys had similar thermo-physical features, it was decided to consider only the last storey for the purpose of the present study because it is the most sensitive to outdoor conditions. Each piece in the apartment i.e. bedroom, living room, and bathroom was treated as a separate zone. The time step of the simulation has been set to 15 min.The agreement between measured and simulated indoor temperature values at every hour was evaluated with the Coefficient of Variation of the Root Mean Square Error (CV(RMSE)) and Mean Absolute error (MAE).

For assessing the thermal comfort, international adaptive comfort standard methodologies such as EN 16798 and ASHRAE 55 as well as PMV were used to measure and to compare indoor comfort in the apartments.

Preliminary Results and Conclusions

(max 200 words)

After making necessary adjustments to the model, the co-simulation model was calibrated to the lowest (CV(RMSE)) values, between 3 and 5%, on indoor temperatures in the living rooms of 3 apartments and stairwell. Analysing indoor temperature of calibrated simulation building with adaptive thermal comfort indices showed that apartments and stairwell in the last floor of the building experienced higher temperatures than the maximum allowable operative temperature for category I and II of EN 16798 and ASHRAE 55 category of acceptability of 80 and 90% up to 5% of the studied period. Passive strategies such as adjusting the openness ratio of windows at night and day (natural ventilation) and closing window shutters to 0.9 i.e. ratio of no-transparent area during the day proved to reduce overheating risks for category I and II of EN 16798 and ASHRAE 55 acceptability category of 80% but not enough for acceptability category of 90%. The latter may need to use mechanical means to reduce overheating risks.

Main References

(max 200 words)

Dols, W.S., and Polidoro, B.J. (2015). CONTAM User Guide and Program Documentation Version 3.2 (Na-tional Institute of Standards and Technology)

ASHRAE-55-2017, «Thermal Environmental Conditions for human occupancy,» Atlanta, 2017.

Bienvenido-Huertas, D., Sánchez-García, D., Rubio-Bellido, C., and Oliveira, M.J. (2020). Influence of adap-tive energy saving techniques on office buildings located in cities of the Iberian Peninsula. Sustain. Cities Soc. 53, 101944

 
13:00 - 14:30Session W2.3: Buildings paving the way for the energy transition
Location: Concert Hall - Studio 1
Session Chair: Alessia Arteconi, KU Leuven
Session Chair: Wim Plokker, Vabi
Concert Hall - Studio 1 
 
13:00 - 13:18

A low-order semi-physical borefield model for optimal control applications

Iago Cupeiro Figueroa1, Lieve Helsen1,2

1KU Leuven, Belgium; 2Energyville, Belgium

Aim and Approach

(max 200 words)

The following research presents a new borefield model for optimal control applications. The proposed model uses a resistance capacitance (RC) network to model the ground. The first nodes of the ground model, which capture the short-term dynamics, are parametrized based on the physical properties of the ground and the borehole. The other nodes, which capture the long-term dynamics, are parametrized based on a fitting procedure that uses information from the borefield characteristic thermal response (i.e., the g-function [1]).

Scientific Innovation and Relevance

(max 200 words)

In the literature, other approaches can be found for control-oriented modeling of borefields. Data-driven models have the drawback that they require a large amount of data [2]. RC ground models impose a fixed temperature at one of the network ends, capturing only the short-term dynamics and disregarding the borehole interactions [3]. Finally, load-aggregation formulations require a large number of states to capture the load history information [4]. The proposed model captures the long-term behaviour of the borefield relying on its characteristic g-function (i.e., no monitoring data but geometrical and physical information of the borefield is required) and using a low number of states.

Preliminary Results and Conclusions

(max 200 words)

The model fitting procedure is parametrized as a function of the number of states to assess the minimum level of detail needed. Based on a step-response test, it is found that 4 states are enough to capture the long-term dynamics. An excessive number of states can lead to overfitting. The proposed RC model is implemented using Modelica and validated against the IBPSA library borefield model [5] for the short- and the long- term range. The model provides good accuracy with a maximum error under 0.5 °C in the short-term and 0.1 °C in the long-term for a number of states lower than 10 for a step-response and periodic pulse case studies.

Main References

(max 200 words)

[1] Eskilson, P. (1987). Thermal analysis of heat extraction boreholes. PhD thesis

[2] Atam, E., Schulte, D. O., Arteconi, A., Sass, I., & Helsen, L. (2018). Control-oriented modeling of geothermal borefield thermal dynamics through Hammerstein-Wiener models. Renewable Energy, 120, 468-477.

[3] Cupeiro Figueroa, I., Picard, D., & Helsen, L. (2020). Short-term modeling of hybrid geothermal systems for Model Predictive Control. Energy and Buildings, 109884.

[4] Laferrière, A., & Cimmino, M. (2018). Model predictive control applied to residential self-assisted ground source heat pumps.

[5] Laferrière, A., Cimmino, M., Picard, D., & Helsen, L. (2020). Development and validation of a full-time-scale semi-analytical model for the short-and long-term simulation of vertical geothermal bore fields. Geothermics, 86, 101788.



13:18 - 13:36

An Open-AI gym environment for the Building Optimization Testing (BOPTEST) framework

Javier Arroyo1,2,3, Carlo Manna2,3, Fred Spiessens2,3, Lieve Helsen1,2

1Department of Mechanical Engineering, KU Leuven, Heverlee, Belgium; 2EnergyVille, Thor Park, Waterschei, Belgium; 3Flemish Institute for Technological Research (VITO), Mol, Belgium

Aim and Approach

(max 200 words)

Building HVAC accounts for 15% of the world final energy use [1]. Their primitive controllers for indoor climate control have shown significant room for improvement, and disagree with the superb developments in state-of-the-art technologies like machine learning. One of the main reasons why these technologies are not yet being adopted by the building sector is the lack of rigorous benchmarking to grow in maturity.

This paper describes an OpenAI-Gym environment for the BOPTEST framework to rigorously benchmark different reinforcement learning algorithms among themselves and against controllers of other type by building simulation. The design philosophy of the environment and its different features are introduced. Finally, the environment is demonstrated in one emulator building model to train a reinforcement learning algorithm and compare it against a classical control logic.

Scientific Innovation and Relevance

(max 200 words)

This paper:

- Introduces an OpenAI-Gym environment that enables the interaction with a set of physics-based and highly detailed emulator building models to implement and assess reinforcement learning for the application of building climate control and demand response.

- Demonstrates the functionality of the framework by implementing and evaluating a state-of-the-art reinforcement learning algorithm to one of the building emulator models.

This work fosters a novel interface that bridges the gap between the latest innovations of machine learning and the field of building energy management. The presented environment can be used to assess the performance of reinforcement learning algorithms when implemented in detailed and reliable building emulator models.

Preliminary Results and Conclusions

(max 200 words)

This paper presents an OpenAI-Gym environment for the BOPTEST framework to enable simulation, evaluation and benchmarking of RL algorithms for building energy management. The framework integrates the main elements that are required by every Gym environment, like the "reset" and "step" methods, along with other useful features to conveniently implement and evaluate "state-of-the-art" RL algorithms for building climate control.

The presented environment heavily relies on the already existing BOPTEST functionality and exploits some of its core components like its API and its KPI calculator module. Definition of the reward function, possibly by the user, is especially taken care of.

Finally, a RL algorithm has been tuned, trained, implemented and benchmarked for different hyperparameter settings of the BOPTEST-Gym environment in order to demonstrate the capabilities of the framework for evaluation and benchmarking.

Main References

(max 200 words)

[1] International Energy Agency. (2019). Global Status Report for Buildings and Construction: Towards a zero-emissions, efficient and resilient buildings and construction sector

[2] Peirelinck, T., Ruelens, F., & Decnoninck, G. (2018). Using reinforcement learning for optimizing heat pump control in a building model in Modelica. 2018 IEEE International Energy Conference, ENERGYCON 2018, 1–6. https://doi.org/10.1109/ENERGYCON.2018.8398832

[3] Dulac-Arnold, G., Mankowitz, D., & Hester, T. (2019). Challenges of Real-World Reinforcement Learning (2019), RL4RealLife Workshop in the 36th International Conference on Machine Learning (ICML) 2019.

[4] Blum, D., Jorissen, F., Huang, S., Chen, Y., Arroyo, J., Benne, K., and Li. Y. (2019). Prototyping the BOPTEST Framework for Simulation-Based Testing of Advanced Control Strategies in Buildings. In proceedings of the 16th IBPSA Conference, Rome.



13:36 - 13:54

Open and Reproducible Use Cases for Energy (ORUCE) methodology in systems design and operation: a dwelling photovoltaic self-consumption example.

Sacha Hodencq, Benoit Delinchant, Frederic Wurtz

Univ. Grenoble Alpes, CNRS, Grenoble INP*, G2Elab, 38000 Grenoble, France

Aim and Approach

(max 200 words)

The development of low-carbon and decentralized renewable energies in the struggle against climate change, especially in urban areas where more than half of the global primary energy is consumed, raises the following question: how to design an energy project and manage energy flows in order to be optimal from ecological and financial points of view? One way to help stakeholders in this task is to provide open energy modelling environments. In this article, we present an Open and Reproducible Use Case for Energy (ORUCE) based on open data, models and tools for the optimal design and operation of an energy system. The use case is the one of a dwelling with self-consumption of photovoltaic (PV) energy and battery storage use. Two free and open source software will be used: NoLOAD for the design, with a focus on both Life Cycle Assessment (LCA) and energy coverage, and OMEGAlpes for the energy management across a year. Providing an ORUCE makes the study reproducible and available for modifications and derived analysis, in addition to making the models easy to grasp.

Scientific Innovation and Relevance

(max 200 words)

Historical energy system modelling as well as current mainstream approaches are closed and proprietary, even if open energy modelling has a promising emergence (Pfenninger et al. 2018). Open energy modelling actually includes many interests: first, it leads to an improved quality of science through transparency and peer reviewing, avoiding errors, biases or even fraud (Pfenninger et al. 2017). An open and reproducible research reduces parallel efforts and enables to share methods and quantitative work with policy makers, when institutions are increasingly asking for transparency. Finally, openness provides trust and legitimacy for scientific arguments in the public debate over the energy transition (Morrison 2018).

Open energy modelling processes have been described in the literature (Pfenninger et al. 2017; Morrison 2018; Hülk et al. 2018) as going from open data sets including data points and metadata, being processed and used with study assumptions for the open model formulation and solving. The model output and interpretation can be shared in open access scientific publication as well as public communication. We propose an ORUCE definition, method, and an actual example to put this process into practice and make the dwelling photovoltaic self-consumption example reproducible and available for improvements.

Preliminary Results and Conclusions

(max 200 words)

The full article will present the design of a dwelling self-consumption of photovoltaic energy with battery storage according to LCA and energy coverage objectives on the one hand, and its energy management across a year on the other hand.

The open tools, models and scenarios used for the study are directly available in the code repository as source code, but also as Jupyter Notebooks, i.e. documents that contain live code, equations, visualizations and narrative text that can be freely used online. Notebooks include many interests: it capitalizes the results of the study, and the way those results were found as well. Moreover, users can modify them, contribute to the code open development, and distribute their results.

We define Open and Reproducible Use Cases for Energy (ORUCE) as notebooks based on open data and open source tools, clearly presenting the method and assumptions used to obtain and present the results, and ideally linked to open edition publications. These ORUCE can be made available, used and broadcasted in open energy platforms.

ORUCE nourish openness in energy modelling and provide actual case studies, thus leading to better science and cooperation between researchers themselves as well as with citizens and policy makers.

Main References

(max 200 words)

Hülk, Ludwig, Berit Müller, Martin Glauer, Elisa Förster, and Birgit Schachler. 2018. ‘Transparency, Reproducibility, and Quality of Energy System Analyses – A Process to Improve Scientific Work’. Energy Strategy Reviews 22 (November): 264–69. https://doi.org/10.1016/j.esr.2018.08.014.

Morrison, Robbie. 2018. ‘Energy System Modeling: Public Transparency, Scientific Reproducibility, and Open Development’. Energy Strategy Reviews 20 (April): 49–63. https://doi.org/10.1016/j.esr.2017.12.010.

Pfenninger, Stefan, Joseph DeCarolis, Lion Hirth, Sylvain Quoilin, and Iain Staffell. 2017. ‘The Importance of Open Data and Software: Is Energy Research Lagging Behind?’ Energy Policy 101 (February): 211–15. https://doi.org/10.1016/j.enpol.2016.11.046.

Pfenninger, Stefan, Lion Hirth, Ingmar Schlecht, Eva Schmid, Frauke Wiese, Tom Brown, Chris Davis, et al. 2018. ‘Opening the Black Box of Energy Modelling: Strategies and Lessons Learned’. Energy Strategy Reviews 19 (January): 63–71. https://doi.org/10.1016/j.esr.2017.12.002.



13:54 - 14:12

Is your building automation and control system properly designed and installed?

Muhyiddine Jradi

University of Southern Denmark, Denmark

Aim and Approach

(max 200 words)

Considering the urgent need and the large technical potential, an innovative holistic tool, IBACSA, is designed and developed, providing a first-of-its kind instrument for building automation and control systems assessment and smartness evaluation. IBACSA development is carried out as one of the deliverables of the research project BuildCOM - Automated Auditing and Continuous Commissioning of Next Generation Building Management Systems, supported by the Danish Energy Agency through the EUDP program.

Regarding the auditing and evaluation methodology, IBACSA employs a hybrid qualitative-quantitative multi-criteria holistic framework, considering eight major building domains: Heating, Domestic Hot Water, Cooling, Ventilation, Lighting, Dynamic Envelope, Electricity and Monitoring and Control. Each domain includes a set of services, defined based on the Standard EN15232 dealing with building automation and control systems. The total number of services is 60, where each service is characterized by different levels of control functionalities.

In auditing the BACS using IBACSA, the assessor will be evaluating the 60 services, choosing the right control level for each service. IBACSA evaluates the BACS and quantify the impact of the selected control levels against five major impact criteria: (1) Energy efficiency, (2) Maintenance and fault prediction, (3) Energy flexibility, (4) Comfort and (5) Information to occupants.

Scientific Innovation and Relevance

(max 200 words)

With the building sector digitalization and the huge rise in the number of installed sensors, smart meters and IoT devices, Building Automation and Control Systems (BACS) are to play key role in the foreseen future. Thus, considering the key role of the buildings stock in the energy sector along with the large potential of improving the building energy performance and optimizing the systems operation, a well-designed and properly installed and operated BACS is critical to achieving current and future energy efficiency and environmental goals set by the countries worldwide.

The trend in building commissioning is that this process is carried out on the whole building level, evaluating if the building envelope is living up to the standards and that the predicted energy consumption is in line with the building regulations. However, there is an overall lack of information and frameworks aiding in the evaluation of the BACS and ensuring that such systems are properly designed and installed. In addition, there is a need for user-friendly and comprehensive tools and instruments aiding the decision making on the energy effective and optimal design and installation of BACS along with allowing auditing and evaluating various building services and the overall building smartness.

Preliminary Results and Conclusions

(max 200 words)

IBACSA evaluation matrix aims at evaluating each domain by itself allowing quick identification of poorly performing building domains across all impact criteria. So, each of the eight domains is evaluated and scored against each of the five impact criteria in addition to an overall score provided for each domain. In addition, the evaluation matrix also provides an overall assessment of the BACS with one overall score against each of the five impact criteria. Thus, IBACSA provides the auditor with a flexibility to consider different evaluation impacts and it is up to the interest of the auditor to consider what is more important.

To allow building consultants, researchers and end-users to fully benefit from IBACSA implementation in case study buildings, the tool is compiled in a standalone desktop executable application allowing for wide distribution and flexible use. The tool consists of a user-friendly interface along with graphical elements and tabs. In selecting services control levels, a simple drop-down approach is employed. In addition, IBACSA aids the user with the decision-making process in terms of retrofitting the current BACS by allowing very simple evaluation and comparison of the impacts of BACS functionalities selected.

Main References

(max 200 words)

Engelsgaard, S., Alexandersen, E.K., Dallaire, J., Jradi, M. (2020). IBACSA: An interactive tool for building automation and control systems auditing and smartness evaluation, Building and Environment 184, 107240.

European Technical Standard EN 15232, Energy Performance of Buildings—Impact of Building Automation, Control, and Building Management (2nd ed.), CEN, Brussels (2012)

 
13:00 - 14:30Session W2.4: Climate change and bioclimatic design
Location: Concert Hall - Studio 2
Session Chair: Shady Attia, Univeristé de Liège
Session Chair: Yasuyuki Shiraishi, The University of Kitakyushu
Concert Hall - Studio 2 
 
13:00 - 13:18

Adapting French buildings to future climate: Passive design optimisation

Anaïs Machard1,2, Christian Inard1, Jean-Marie Alessandrini2, Charles Pelé2, Jacques Ribéron3

1Laboratoire des Sciences de l’Ingénieur pour l’Environnement (LASIE, UMR CNRMS 7356), La Rochelle Université, 23 Avenue Albert Einstein, 17000 La Rochelle, France; 2Département Energie et Environnement, Centre Scientifique et Technique du Bâtiment (CSTB), 84 Avenue Jean Jaurès, Champs-sur-Marne, 77447 Marne-la-Vallée CEDEX 2, France; 3Département Santé et Confort, Centre Scientifique et Technique du Bâtiment (CSTB), 84 Avenue Jean Jaurès, Champs-sur-Marne, 77447 Marne-la-Vallée CEDEX 2, France;

Aim and Approach

(max 200 words)

In France, buildings have historically been designed to withstand cold winter. In recent years, “bioclimatic” design has become mandatory in the national thermal regulation, to reduce the heating consumption. However, with climate change and more frequent projected heatwaves, there is a new need to design buildings to also be able to support warm summers and not overheat. Future buildings should be able to be resilient to the outdoor changing climate, and the adaptation should start from the design phase. The dangerous predicted increase of air-conditioning penetration and use reinforces the exigency to propose a design consuming as less energy as possible to reduce greenhouse gases emissions. With the development of climate projections and the recent availability to use these future climate data for building thermal simulations, conceiving buildings today to be adapted for the climate of tomorrow is feasible. In this paper, we introduce a new paradigm: Is it possible to design a building that will be adapted both to winter and summer? Are passive cooling solutions enough to maintain acceptable indoor environment comfort level? In our analysis, we propose to optimize a low-energy residential building case-study for future summer conditions, including future heatwaves sequences.

Scientific Innovation and Relevance

(max 200 words)

The algorithm NSGA-II is used to test different building combinations such as thermal inertia, proper use of solar shading, nocturnal ventilation, cool paints, earth-to-air heat exchanger, and indirect adiabatic cooling in different French cities, while the building is modelled with the software EnergyPlus. The objectives are to reduce summer thermal discomfort while reducing the uncertainty related to the future climate projections from CORDEX datasets. The outcomes of the study give indications of best strategies to implement in different locations, while the overall methodology can be re-used to consider risk and uncertainties related to future climate conditions during the design process.

Preliminary Results and Conclusions

(max 200 words)

It is very challenging to propose an optimised passive building design to future heatwaves in France. Traditional summer bioclimatic design, such as the use of solar shading, nocturnal ventilation and cool paints is enough to maintain acceptable indoor level conditions under a future typical climate of an average climate model, but not under higher projections such as future intense heatwaves from high climate models. In order to provide a resilient design to different sorts of future climate conditions, the additional use of semi-active cooling solutions such as earth-to-air heat exchanger, and indirect adiabatic cooling is necessary.

Main References

(max 200 words)

Moazami, A.; Carlucci, S.; Nik, V.M.; Geving, S. Towards climate robust buildings: An innovative method for designing buildings with robust energy performance under climate change. Energy Build. 2019, 202, 109378.

Machard, A.; Inard, C.; Alessandrini, J.M.; Pelé, C.; Ribéron, J. A Methodology for assembling future weather files including heatwaves for building thermal simulations from the European Coordinated Regional Downscaling Experiment (EURO-CORDEX) climate data. Energies 2020,13, 3424.

Ascione, F.; Bianco, N.; Francesca De Masi R. ; Maria Mauro, G. ; Vanoli G.P. Resilience of robust cost-optimal energy retrofit of buildings to global warming: A multi-stage, multi-objective approach. Energy and Buildings. 2017, 153, pages 150-167

Chinazzo, G.; Rastogi P.; Andersen, M.; Robustness assessment methodology for the evaluation of building performance with a view to climate uncertainties. 14th International Conference of the International Building Performance Simulation Association, At Hyderabad, India. 2015

Lapisa, R.; Bozonnet, E.; Salagnac, P.; Abadie M.O.; Optimized design of low-rise commercial buildings under various climates – Energy performance and passive cooling strategies. Building and Environment. 2018, 132, pages 83-95



13:18 - 13:36

Assessing the relevance of updated climate files in the simulation of residential buildings located in semi-arid regions

Emanuela Giancola, María Nuria Sánchez, Helena López, Jose Antonio Ferrer, María José Jiménez, Silvia Soutullo

Energy efficiency in buildings research unit, CIEMAT, Spain

Aim and Approach

(max 200 words)

Real building energy consumption is one of the high-priority research and innovation topics in the scientific community [1]. This work quantifies the climate trends registered on the energy performance of residential buildings located in semi-arid regions. The climate of this zone is characterized by hot-dry summers and cold-dry winters with mean annual temperatures below 18ºC and low annual precipitations. This study contributes to improve the knowledge that the global warming has on the building demands under severe climate conditions.

A generic building case placed in the desert of Tabernas (Almería, Spain) has been analyzed. Firstly, one representative residential building has been modelled with the software TRNSYS [2], according to the local characteristics. To evaluate the annual thermal loads, seasonal temperature set-points have been fixed. Secondly, a parametric evaluation has been developed considering different Spanish building regulations, two boundary conditions (4 and 2 external façades) and three climate years. The meteorological conditions have been assessed through the use of one long-term experimental file for Tabernas [3], and two synthetic years downloaded on the Energy plus [4] and the Spanish building code websites [5]. Finally, the obtained results have been compared to quantify the climate trends produced in different building configurations.

Scientific Innovation and Relevance

(max 200 words)

The climate change impact is a major fact affecting many cities, their communities and infrastructures, and especially vulnerable urban populations. This research is focused on the impact that outdated climate files have on the energy simulation of a generic residential building model. The use of this non-realistic datasets produces many uncertainties into the modelling process [6]. To quantify this deviation, one long-term experimental climate file and two representative climate files have been used as inlet information. The comparison between them gives an idea of how the climate change modifies the patterns of the building energy performance. This issue has been discussed in recently published papers ([7], [8]).

This article highlights the necessity of using updated meteorological information to reduce the uncertainties produced by the input data in the simulation process. This can help governments to better adjust its policies and action plans to the current weather conditions.

Although this study has been carried out for a specific case located in the desert of Tabernas (Almería, Spain), generic buildings and normative values for the building envelope have been selected in order to extend the obtained results to buildings with similar construction characteristics located in similar climate zones (BWk Köppen Geiger classification).

Preliminary Results and Conclusions

(max 200 words)

An initial study analyzes the climate trend in a semi-arid region identifying the tendencies over the last decade by an experimental campaign of 10 years carried out by CIEMAT in Tabernas. Long-term experimental database present warmer (+0.3°C) and drier (-16%) summers compared to the Energy plus synthetic year. However, the Spanish building code synthetic summer is significantly colder (-1.6°C) and wetter (+4%). This tendency is strongly supported by the number of tropical nights, around 65 on both experimental and Energy plus years, and clearly higher than 18, the corresponding value for Spanish building code year. However, Energy plus synthetic year presents the warmest annual climate.

Subsequently, the climate impact on the building thermal conditioning is assessed by means of dynamic simulations with TRNSYS. The building configuration with 4 external façades demands more annual thermal loads than the 2 façades configuration. The implementation of more currently constructive normative strongly reduces the annual thermal loads. The climate file provided by the Spanish normative obtains the highest annual loads, followed by the experimental file. The climate file provides by EnergyPlus website reaches the lowest annual loads. These differences are very low as far as stricter constructive conditions are implemented in the building configuration.

Main References

(max 200 words)

[1] EBC Executive Committtee. 2019. International Energy Agency. Strategic Plan 2019-2024. Energy in Buildings and Communities Technology Collaboration Programme.

[2] Transient System Simulation Tool (TRNSYS). Available online: https://www.trnsys.com.

[3] Sánchez, M.N., Soutullo, S., Olmedo, R., Bravo, D., Castaño, S., Jiménez, M.J., 2020. An experimental methodology to assess the climate impact on the energy performance of buildings: A ten-year evaluation in temperate and cold desert areas. Applied Energy. 264, 114730.

[4] Energy Plus Weather Database. Available online: https://energyplus.net/weather-region/europe_wmo_region_6/ESP%20%20.

[5] Spanish Building Code. Available online: https://www.codigotecnico.org/index.php/menu-ahorro-energia.html.

[6] W. Tian, Y. Heo, P. de Wilde, Z. Li, D. Yan, C.S. Park, X. Feng, G Augenbroe. 2018. A review of uncertainty analysis in building energy assessment. Renewable and Sustainable Energy Reviews. 93, pp. 285–301.

[7] Soutullo S, Giancola E, Jiménez MJ, Ferrer JA, Sánchez MN. How Climate Trends Impact on the Thermal Performance of a Typical Residential Building in Madrid. Energies 2020;13(1):237.

[8] Wang, L.; Liu, X.; Brown, H. Prediction of the impacts of climate change on energy consumption for a medium-size office building with two climate models. Energy Build. 2017, 157, 218–226.



13:36 - 13:54

Climate change impact on the future performance of Nearly Zero Energy buildings: A case study base analysis

Mamak Pourabdollahtootkaboni, Giovanna De Luca, Ilaria Ballarini, Vincenzo Corrado

Politecnico di Torino, Turin, Italy

Aim and Approach

(max 200 words)

This paper investigates the effects of climate changes on energy performance and overheating risk of a nearly zero energy building (nZEB) in different climate zones in Italy. The study is carried out by analyzing the nZEB requirements such as the annual energy needs for space heating and space cooling (EPH,nd and EPC,nd, respectively), the overall annual total primary energy (EPgl,tot), the mean overall seasonal efficiencies of technical building systems and renewable energy ratio, under different scenarios. “Representative Concentration Pathways (RCPs)”8.5 (business as usual) of emission and concentration scenarios according to the fifth assessment report of the intergovernmental panel on climate change [1], have been applied in this study. Dynamically down-scaled future hourly weather data from the regional climate models (GERICS-REMO 2015) are used in this work to create future typical meteorological year (TMY). To reduce the climate model uncertainties a distribution based, multivariate method for bias-correction of weather data is implemented [2]. Energy simulations are carried out using Energy Plus for the mid-term (from 2056 to 2075) and long term (from 2081 to 2100) period.

Scientific Innovation and Relevance

(max 200 words)

Recent studies reveal that climate change will shift the building's performance pattern in the future. According to the fifth assessment report of the intergovernmental panel on climate change [1], this trend seems to be inexorable. The temperature increase will endure even by assuming the immediate stop of the greenhouse gas emissions due to the already present greenhouse gases in the atmosphere. To counteract this trend, the Energy and Climate Policy Framework for 2030 [3] sets key targets to cut at least 40% in green gas emissions (compared to 1990 levels). Considering building stock large share of Europe's final energy consumption and CO2 emissions, the concept of nearly-zero energy buildings (nZEB) has received considerable attention. However, the performance of nZEBs in the future has not yet been investigated sufficiently. The climate is changing and the compliance with nZEB requirements may not be a guarantee of energy performance and indoor environmental quality. Considering the long-life span of buildings, the performance of nZEBs should be analysed using future weather data, to ensure energy efficiency, sustainability, and climate resilience over time.

Preliminary Results and Conclusions

(max 200 words)

The preliminary results indicate that climate change affects the energy balance and thermal comfort of the nZEB, however, the extent varies among the different climate regions and future scenarios. The simulations show that the increases in cooling energy need overcome the decreases in heating energy need. The electricity use will increase due to more hours out of thermal comfort. Although the energy output of the PV panel system will be increasing in the future, buildings will miss the target of meeting nearly zero energy and the new configuration is needed to keep nZEB goals in the future. These results highlight the significance of considering future weather for energy performance assessment of nZEBs and establishing building adaptation measures for climate change beside nZEB measures, to ensure a holistic approach.

Main References

(max 200 words)

[1] Symon, Carolyn. "Climate change: actions, trends and implications for business. The IPCC fifth assessment report, Working Group 1." (2013): 524-82.

[2] Cannon, Alex J. "Multivariate quantile mapping bias correction: An N-dimensional probability density function transform for climate model simulations of multiple variables." Climate dynamics 50.1-2 (2018): 31-49.

[3] European Commission, COM, 15 final, Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions, A policy framework for climate and energy in the period from 2020 to 2030, 2014, 2014, https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52014DC0015&amp;from=EN



13:54 - 14:12

The impact of a high-end climate change scenario on the energy consumption of a Flemish office building

Delphine Ramon, Karen Allacker

Department of Architecture, Faculty of Engineering Science, KU Leuven, Belgium

Aim and Approach

(max 200 words)

This paper evaluates the impact of a high-end climate change scenario on the energy consumption for heating and cooling of a Flemish office building. A dynamic building energy simulation is executed with EnergyPlus for a state-of-the-art Flemish office building. Weather data is extracted from a high-resolution climate model for an RCP 8.5 climate change scenario through a typical meteorological year. This model allows to extract weather data on an hourly time resolution and a spatial resolution of 2.8 by 2.8 km. Data is extracted for different locations in Belgium and allows us to analyze broader, regional effects such as distance to the seaside, and orography as well as local effects such as the urban heat island effect. Different locations are selected in Belgium to cover these regional and local effects. The energy consumption is analyzed and validated for the location of the building as well as for other locations in Belgium both for the current and future climate model data. In addition, the change in thermal comfort within the building is analyzed, making use of the Category II limits of the EN 16798-1:2019 standard. The paper will particularly focus on the impact on cooling energy consumption and summer comfort.

Scientific Innovation and Relevance

(max 200 words)

More and more, buildings are analyzed in a future climate context. Also, more and more regional climate model output is used for the weather data of these simulations. Typically, model data with a spatial resolution up to 12.5km is available. The climate model used in this study is a convection-permitting model that typically has a spatial resolution < 4km. At this spatial resolution, the models have a better resolved daily cycle, an explicit representation of the urban heat island effect, and better-resolved land use and orography making them favorable for building energy simulations. The use of climate model data at this spatial resolution in building energy simulations is not known to the authors. Further, evaluations of building performance towards the future in a Belgian context are not elaborated making use of climate model output in dynamic building simulations. These data have an important advantage in comparison to morphing techniques used in weather generator tools, which do not guarantee to keep the physical consistency between weather variables used in the building energy simulation.

Preliminary Results and Conclusions

(max 200 words)

As expected, an increase in cooling load and a decrease in heating load towards the end of this century under a high-end climate change scenario is found. An increase in cooling load up to 20% on monthly basis is found under typical weather conditions for the RCP 8.5 climate change scenario. Under extreme warm weather conditions, an increase of up to 15% is found. Higher increases are found for the office rooms with Southwest orientation. It is expected that due to the system capacity, the increase in the building-specific cooling energy consumption will be smaller but that this will cause an increase in the discomfort. The latter is confirmed in the preliminary results of the full building energy simulation (including the actual HVAC system). Increases of up to 5% were found in cooling energy consumption. However, further verification of the model is needed. Also, the performance will be evaluated across different locations in Belgium. Smaller changes are expected in more rural areas or areas close to the seaside. While bigger changes in discomfort are expected in urban areas.

Main References

(max 200 words)

Nik, V. M. (2016). Making energy simulation easier for future climate–Synthesizing typical and extreme weather data sets out of regional climate models (RCMs). Applied Energy, 177, 204-226.

CEN, E. (2007). 15251, Indoor environmental input parameters for design and assessment of energy performance of buildings addressing indoor air quality, thermal environment, lighting and acoustics. European Committee for Standardization, Brussels, Belgium.

Ramon, D., Allacker, K., De Troyer, F., Wouters, H., & van Lipzig, N. P. (2020). Future heating and cooling degree days for Belgium under a high-end climate change scenario. Energy and Buildings, 109935.

Chow, D. H., & Levermore, G. J. (2010). The effects of future climate change on heating and cooling demands in office buildings in the UK. Building Services Engineering Research and Technology, 31(4), 307-323.

Hosseini, M., Tardy, F., & Lee, B. (2018). Cooling and heating energy performance of a building with a variety of roof designs; the effects of future weather data in a cold climate. Journal of Building Engineering, 17, 107-114.



14:12 - 14:30

Development of a new decision tool for Sustainable COOLing Systems (CORNET SCOOLS)

Jeroen Van der Veken1, Margot De Pauw2

1BBRI, Belgium; 2KCE Thomas More, Belgium

Aim and Approach

(max 200 words)

Due to climate change and increasing frequency of heat waves, cooling in residential buildings gains importance. The most common way of cooling in buildings is active cooling with the use of ‘split units’ or central air-conditioning systems, using an electric compressor and standard refrigerant. However, these systems have a relative high energy consumption, and the European parliament has called a phasedown for many of the refrigerants. Sustainable cooling systems can therefore be a superior alternative for conventional systems. These systems are however not often applied due to a lack of real performance data and guidelines for the correct selection and dimensioning. This problem is addressed by the CORNET SCoolS.

Scientific Innovation and Relevance

(max 200 words)

Key Innovations

• Decision support tool for sustainable cooling systems

• Assessment of summer comfort in dwellings

• Cooling loads room per room

Practical Implications

• The uncertainty about climate projections complicate summer comfort evaluations.

• There exist many methods to assess summer comfort, it is always a good idea to store the (hourly) operative temperatures so that other calculations can be done in post-processing

• Be sure to implement a realistic control algorithm when comparing passive and active cooling systems

Preliminary Results and Conclusions

(max 200 words)

A new decision tool has been made to compare different (sustainable) cooling systems and passive cooling strategies in dwellings. To make it future proof, a new (extreme) climatic data file was constructed. However, the selection of the comfort criteria showed to be difficult.

If adaptive temperature boundaries are uses, as is allowed and described in EN16798-1 (2019), the impact of heat waves is somewhat tempered as the temperature criteria go up as well. However, it is not certain if this can be applied straightforward to residential cases. The authors chose to add the absolute comfort criteria of CIBSE Guide A (2015) and the following comfort classes were determined based on the exceeding hours: good (0h), acceptable (<32h), possible (< 64h), uncomfortable.

In general, the simulations show that a lot of sustainable cooling systems, although their lower specific power, can provide good comfort in most of the residential buildings, provided that passive cooling strategies are applied. Without any cooling system this will become difficult.

Main References

(max 200 words)

CIBSE Guide A: Environmental design (2015)

IEA EBC. (2018). Annex 62 Ventilative Cooling Design Guide.

IEA EBC (2020). Annex 80 Resilient Cooling

EN16798-1. (2019).

ISO 7730. (2005).

Witkamp M.J., Koornneef W., Wijnja L., Kaspers J., van Weele H., Schouten C. & Plokker W. (2019) Themablad thermisch comfort (https://energielinq. stroomversnelling.nl/kwaliteitskaders/nieuwe-methode-voorkomt-oververhitting-woningen/)

 
13:00 - 14:30Session W2.6: The role of occupants
Location: Concert Hall - Kamermuziekzaal
Session Chair: Andrea Gasparella, Free University of Bozen - Bolzano
Session Chair: Damien Picard, KU Leuven
Concert Hall - Kamermuziekzaal 
 
13:00 - 13:18

Mapping the gap in user-related building performance simulation models

Ardeshir Mahdavi, Veselina Bochukova, Christiane Berger

TU Wien, Austria

Aim and Approach

(max 200 words)

Recently, increasing attention is being paid in the building performance simulation research community to the quality and resolution of representations of building users in simulation models (Mahdavi and Tahmasebi 2019). This is reflected in a host of publications and projects with highly diverse starting points, approaches, and results (Yan et al. 2017, Berger and Mahdavi 2020). Whereas such diversity can be productive and fruitful, it may also involve redundancy and lack of strategic orientation. In this context, it is beneficial to reexamine this subject from two complementary directions. One ontological direction, characterized here as "top-down", pursues the required format and dimensions of a generalized representation of building users that could be distilled down as needed to cater for the informational requirements of specific applications. The second direction, which can be seen as "bottom-up", starts by reverse-engineering the occupant-specific input templates of common performance simulations in view of any existing shared features and structure. We suggest that the pursuit of these two directions reveals a discontinuity or gap, indicating that there is not yet a seamless path leading from occupant-centric ontologies to occupant-related model input requirements of common performance simulation tools.

Scientific Innovation and Relevance

(max 200 words)

The building information modeling research and development community has become increasingly cognizant of the following circumstance: To be truly effective, building information models must go beyond the static representation of buildings' constituent physical components (Mahdavi 2020). Rather, the time-dependent dynamics of processes associated with the design, construction, and operation of buildings must be taken into consideration. A major class of such processes involve the patterns of occupants' presence and behavior in buildings. A comprehensive solution for the respective representational challenges must go beyond ad hoc amendments to existing simulation input routines. Toward this end, a seamless transition from a comprehensive ontology of building users down to specific input schema tailored for individual simulation application would be desirable, but currently hampered to a representational discontinuity. The aforementioned concurrent top-down and bottom-up inquiries can help map this gap and hence suggest approaches to close it.

Preliminary Results and Conclusions

(max 200 words)

The work thus far has led to the definition of a general schema that captures the main dimensions of occupant-related information. These include physical data pertaining to position and movement, physiological data pertaining to state of metabolism and adaptation, cognitive data pertaining to formation of impressions and value attributions, as well as event-based data pertaining to human-building interaction processes. The result suggests that, in order to consistently structure the schema, underlying foundational theories are needed that capture building users' relevant patterns of presence and behavior. Moreover, the bottom-up reverse-engineering of existing simulation applications reveals the potential and challenges toward seamless derivation of locally tailored input information from ontologically structured sources of occupant-related information.

Main References

(max 200 words)

Berger, C., and Mahdavi, A. (2020): Review of current trends in agent-based modeling of building occupants for energy and indoor-environmental performance analysis. Building and Environment, 173; 106726.

Mahdavi, A., and Tahmasebi, F. (2019): People in building performance simulation. Building Performance Simulation for Design and Operation - Expanded Second Edition. Hensen, J., Lamberts, R. (Ed.); Routledge, New York, ISBN: 978-1-138-39219-9; pp. 117 - 145.

Mahdavi, A. (2020): Bringing HIM closer to HER. Keynote. Proceedings of SIMAUD: Symposium on Simulation for Architecture and Urban Design. Vienna (Online), 25-26 May 2020. ISBN: 978-1565553712.

Yan, D., Hong, T., Dong, B., Mahdavi, A., D´Oca, S., Gaetani, I., and Feng, X. (2017): IEA EBC Annex 66: Definition and simulation of occupant behavior in buildings. Energy and Buildings, 156; pp. 258 - 270.



13:18 - 13:36

The impact of occupancy prediction accuracy on the performance of model predictive control (MPC) in buildings

Tao Yang, Fisayo Caleb Sangogboye, Krzysztof Arendt, Konstantin Filonenko, Jonathan Dallaire, Mikkel Baun Kjærgaard, Christian Veje

Center for Energy Informatics, University of Southern Denmark, Denmark

Aim and Approach

(max 200 words)

This paper aims to investigate the impact of occupancy accuracy on the performance of MPC-based building control. As an experimental setup, a grey-box model representing the heating, ventilation, and air conditioning (HVAC) system in a case study building is developed and calibrated. Subsequently, a number of 3D stereo-vision cameras is deployed to obtain accurate occupancy counts. Based on the obtained measurements, a data-driven model for predicting occupancy count in simulation is developed. In the evaluation, two MPC-based building controllers with different occupancy accuracy are compared based on multiple shooting optimization algorithm. The first of the compared models uses occupancy estimates from the deployed camera, while the second uses occupancy prediction from the data-driven model. The two MPC-based building controllers are further compared with a conventional rule-based controller in terms of energy consumption and indoor thermal discomfort.

Scientific Innovation and Relevance

(max 200 words)

Globally, buildings are responsible for nearly 40% of total energy consumption among other sectors [1]. MPC is a promising and widely investigated strategy employed in buildings to reduce energy consumption while maintaining thermal comfort. While there exists a wide range of parameters for MPC-based building controls, the accurate estimation of occupancy in buildings constitute a major factor for achieving considerable ambient comfort and energy saving within buildings [2-5]. This paper goes beyond simple analysis of the occupant presence and applies a data-driven approach to accurately predict occupant count and subsequently studies the impact of occupancy accuracy on MPC performance, which contributes to better analyze relationship between occupancy information and MPC performance in buildings.

Preliminary Results and Conclusions

(max 200 words)

The developed grey-box model yields good accuracy of capturing thermal dynamics of the system. Using occupancy estimates from the deployed cameras, an MPC-based controller in contrast to a rule-based controller demonstrates better indoor thermal comfort and higher energy consumption due to that MPC prioritizes thermal comfort (hard constraint) over energy. Comparing MPC with two different occupancy accuracy, occupancy predictions with low accuracy can lead to lower energy consumption at the expense of thermal comfort violations. When increasing optimization horizon, MPC-based controller with more accurate occupancy prediction shows larger energy consumption and improved thermal comfort. Besides, the negative influence of prediction error can be partially mitigated by adopting longer optimization horizons.

Main References

(max 200 words)

[1] Cao, Xiaodong, Xilei Dai, and Junjie Liu. "Building energy-consumption status worldwide and the state-of-the-art technologies for zero-energy buildings during the past decade." Energy and buildings 128 (2016): 198-213.

[2] Amin Mirakhorli and Bing Dong. Occupancy behavior-based model predictive control for building indoor climate - a critical review. Energy and Buildings, 129: 499–513, 2016.

[3] Justin R Dobbs and Brandon M Hencey. Model predictive hvac control with online occupancy model. Energy and Buildings, 82: 675–684, 2014.

[4] Frauke Oldewurtel, David Sturzenegger, and Manfred Morari. Importance of occupancy information for building climate control. Applied energy, 101: 521–532, 2013.

[5] Siddharth Goyal, Herbert A Ingley, and Prabir Barooah. Occupancy-based zone climate control for energy-efficient buildings: Complexity vs. performance. Applied Energy, 106: 209–221, 2013.

[6] K. Arendt and C. Veje, “MShoot: an Open Source Framework for Multiple Shooting MPC in Buildings,” in 16th IBPSA International Conference and Exhibition Building Simulation 2019, Rome, 2-4 September, 2019, 2019.

[7] Antoine Garnier, Julien Eynard, Matthieu Caussanel, and Stéphane Grieu. Predictive control of multizone heating, ventilation and air-conditioning systems in non-residential buildings. Applied Soft Computing, 37: 847–862, 2015.



13:36 - 13:54

Consequences-based graphical model for contextualized occupants’ activities estimation in connected buildings

Huynh Phan1, Thomas Recht1, Laurent Mora1, Stéphane Ploix2

1I2M Bordeaux, University of Bordeaux, CNRS, Arts et Metiers Institute of Technology, Bordeaux INP, F-33400 Talence, France; 2G-SCOP, Grenoble Institute of Technology, UMR CNRS 5272, 46 Avenue Felix Viallet, 38031 Grenoble Cedex 1, France

Aim and Approach

(max 200 words)

Occupants' activities are addressed as important factors resulting in the discrepancy between simulated and actual energy consumptions in residential buildings. Many models with statistical data are proposed to better estimate the activities of occupants than conventional approaches. However, these models are hybrid of the statistical data, which contains the information of many dwellings with different habits and characteristics, and not entirely sufficient to represent contextualized activities in a particular household. To solve this problem, data-driven approaches with machine learning techniques are proposed to estimate the activities based on the data measured from on-site sensors. However, they are black-box approaches and difficult to understand. It is preferable to propose an understandable model, which is able to estimate and evaluate the contextualized activities in a particular household. In this contribution, a general approach model taking into account a particular context is proposed to estimate and predict the occupants’ activities in a specific household. Specifically, many sensors (CO2, temperature, motions, etc.) are installed to capture the data in the household. Then, combining with the context information, the necessary features are extracted from measured data and are used to build a consequences-based Bayesian Network, which is understandable, and flexible for the contextualized activities estimation.

Scientific Innovation and Relevance

(max 200 words)

Recently, statistical approach is the most popular approach for occupants’ activities estimation in buildings. [1,6] used statistical models to estimate the activities using the characteristics of both buildings and households. Though, their models are hybrid of statistical data of different dwellings and not sufficient to estimate and evaluate the contextualized activities in a particular household. To deal with it, [2,7] applied data-based models with machine learning techniques to estimate activities using the measurement data. However, they do not provide understandable outputs and are not adaptable to context’s changes. Otherwise, [3,4] proposed agent-based models to simulate the activities of windows/doors. An agent perceives the space’s conditions and executes activities to achieve its predefined comfort. However, agent-based models are too complex with many agents. Besides, [5] built Bayesian Network (BN) to estimate the activities of doors based on the measurement data and expert knowledge. BN is an understandable, easy adaptable model for activities estimation in a particular household. However, all studies focus on simple activities (actions of windows/door, presence, etc.) and the structure of the BN is difficult to define. This study proposes a BN with an expert structure for contextualized activities estimation from measurement data, in a specific household.

Preliminary Results and Conclusions

(max 200 words)

A general approach has been proposed in this contribution to estimate the daily activities in a residential building. Dynamic Time-Series Clustering and expert discretization techniques are used to extract features from variables while Information Gain is used for the necessary features selection. Consequences-based Bayesian Network is used as an estimation model based on an expert structure, which is determined by the consequences of the activities. Finally, cross-validation and F1-score are used to validate the proposed model in the testing data. The proposed model was used to estimate some activities such as cooking breakfast, cooking lunch, washing dishes, etc. The testbed is a detached house in France, which includes 5 household members and 11 rooms. The data was collected from numerous installed sensors of ambient, power, motion, windows/doors contacts, etc. The labels of activities were collected for two months by a self-developed mobile application. In this contribution, the activity cooking lunch in the kitchen is presented. Data set covers 45 weekdays from 09/12/2019 to 30/02/2020 (labels collection period). Results show that cooking lunch is mainly linked to the patterns of the usages of frequently involved appliances (microwave, toaster). Cross-validation is used and F1-score is approximately 91%.

Main References

(max 200 words)

1. Dorien Aerts. 2015. Occupancy and Activity Modelling for Building Energy Demand Simulations, Comparative Feedback and Residential Electricity Demand Characterisation. PhD Thesis, Vrije Universiteit Brussel.

2. Alaa Alhamoud, Pei Xu, Frank Englert, et al. 2015. Extracting Human Behavior Patterns from Appliance-level Power Consumption Data. Wireless Sensor Networks, Springer International Publishing, 52–67.

3. Yoon Soo Lee and Ali M. Malkawi. 2014. Simulating multiple occupant behaviors in buildings: An agent-based modeling approach. Energy and Buildings 69: 407–416.

4. Khadija Tijani, Ayesha Kashif, Stéphane Ploix, Benjamin Haas, and Julie Dugdale. 2015. Comparison between purely statistical and multi-agent based ap-proaches for occupant behaviour modeling in buildings. arXiv:1510.02225 [cs].

5. Khadija Tijani, Quoc Dung Ngo, Stéphane Ploix, Benjamin Haas, and Julie Dugdale. 2015. Towards a General Framework for an Observation and Knowledge based Model of Occupant Behaviour in Office Buildings. Energy Procedia 78: 609–614.

6. Urs Wilke. 2013. Probabilistic Bottom-up Modelling of Occupancy and Activities to Predict Electricity Demand in Residential Buildings. .

7. Suyang Zhou, Zhi Wu, Jianing Li, and Xiao-ping Zhang. 2014. Real-time Energy Control Approach for Smart Home Energy Management System. Electric Power Components and Systems 42, 3–4: 315–326.



13:54 - 14:12

Multi-Agent based simulation of human activity for building and urban scale assessment of residential load curves and energy use

Mathieu Schumann1,5, Quentin Reynaud2, Nicolas Sabouret3, François Sempé6, Benoit Charrier1,5, Jérémy Albouys1,3,4,5, Yvon Haradji1, Christian Inard4,5

1EDF R&D, Palaiseau, France; 2QRCI, Clermont-Ferrand, France; 3LIMSI-CNRS, Univ. Paris-Sud, Univ. Paris-Saclay, Orsay, France; 4LaSIE, CNRS, La Rochelle Université, La Rochelle, France; 54evLab, EDF R&D, CNRS, LaSIE, La Rochelle Université, La Rochelle, France; 6FSCI, Paris, France

Aim and Approach

(max 200 words)

Because of the crucial impact of human activity on energy consumption (Janda, 2011), many building and urban energy models integrate human activity modeling. An increasing number of research works use Time Use Surveys (Chenu et al, 2006) and stochastic person-based approaches to generate occupancy profiles, window uses, or activity chronograms (Baetens et al, 2016). The goal of this paper is twofold: 1/ to discuss the limits of the existing state-of-the-art approaches on human activity modeling, and 2/ to present our modeling approach: an agent-based, individual-centered simulation of human activity, taking individual decisions and interactions between individuals into account to produce activity diagrams that are consistent at the household scale. Associated with a population generator, and by linking the simulated activity with appliance use, one of the main applications is the calculation of residential households load curves.

Our work puts the simulation of human activity and everyday life decision-making processes at the center of energy consumption, thermal comfort or indoor air quality assessments in households. This approach has its roots in ergonomics studies, which demonstrated the ability of multi-agent systems to simulate a realistic human activity, using innovative validation methodologies such as participatory simulations with real households (Haradji et al, 2012).

Scientific Innovation and Relevance

(max 200 words)

The analyzed approaches appear to be insufficient to account for the dynamics of individual and collective activity and its impact on energy consumption (Happle, 2018), particularly as households and energy communities become more actively integrated in smart grids and involved in flexibility, collective self-consumption or energy exchange schemes. Such configurations involve individual and collective decision-making, as well as the management of new appliances such as electric vehicles.

We suggest that the co-simulation of autonomous agents, whose activities are built upon statistical data (e.g. Time Use Surveys), with building and appliance models (Plessis, 2014) can effectively tackle these new challenges. We propose a fine-grained, 1 minute time step household simulation, able to perform population-wide yearly simulations. Our agent-based model can reach a satisfying level of diversity in human activities, and it supports interactions between autonomous agents and a changing environment (e.g. activity priorities, incentives, energy prices). This model accounts for emerging, reactive, adaptive, and collective behaviors. Moreover, it allows to deal with many human behavioral aspects (e.g. presence, heating adjustment, housing ventilation) within the same decisional process, bringing consistency to the role of occupant in energy assessments.

Preliminary Results and Conclusions

(max 200 words)

We present the agent-based SMACH platform (SiMulation of human Activity and Consumption in Households) (Haradji et al, 2018). We show how the modeling of occupants as intelligent autonomous agents accounts for the individual and collective dynamics of daily life and the related energy consumption, modeled as the result of the interactions between agents and the household’s electrical appliances. We demonstrate how the latest developments of the SMACH simulation platform, combining population synthesis, simulation of individual and collective activities as well as electric mobility, answer some of the challenges related to the role of occupants in energy consumption (Happle, 2018). Especially, we show that multi-agent modeling offers a high degree of modularity due to the internal capabilities of the agents to organize themselves, plan their day, or react to events or changes in the environment. This approach is also explicit, and makes it possible to explain why, when, how and with whom the simulated energy consumption is performed. We illustrate the validation approaches and variety of uses of this model in energy questions and engineering applications such as load curve calculation, at an individual household scale as well as at the population scale.

Main References

(max 200 words)

Janda, Kathryn B. (2011). Buildings Don’t Use Energy: People Do. Architectural Science Review 54 (1): 15–22

Chenu, A. and Lesnard L. (2006) Time Use Surveys: A Review of Their Aims, Methods, and Results. European Journal of Sociology 47 (3): 335–59.

Baetens, R. and Dirk S. (2016). Modelling Uncertainty in District Energy Simulations by Stochastic Residential Occupant Behaviour. Journal of Building Performance Simulation 9 (4)

Haradji Y., Poizat G., Sempé F (2012) Human Activity and social simulation. Proceedings of the 4th Advances in Human Factors and Ergonomics Conference, San Francisco, California, USA

Plessis, G., Edouard A., Haradji, Y. (2014). Coupling Occupant Behaviour with a Building Energy Model - A FMI Application. 10th International Modelica Conference 96:321–26 Lund, Sweden

Haradji Y. et al, (2018) From modeling human activity to modeling for social simulation: between realism and technological innovation. Activités 15-1

Happle G., Fonseca J. A. and Schlueter A. (2018) A review on occupant behavior in urban building energy models. Energy and Buildings, vol. 174. Elsevier Ltd, pp. 276–292



14:12 - 14:30

The formulation of a reference load curve to measure energy flexibility

Muhammad Salman Shahid1, Benoît Delinchant1, Béatrice Roussillon2, Frédéric Wurtz1, Daniel Llerena2

1G2Elab, 21 Rue des Martyrs, CS 90624, 38031 Grenoble CEDEX 1, France; 2GAEL, 1241 Rue des Résidences, 38400 Saint-Martin-d'Hères, France

Aim and Approach

(max 200 words)

Energy consumers have a degree of choice to implement indirect energy flexibility to mitigate network congestion during the intermittence of renewable production. It is essential to measure the impact of each alert for each consumer. This abstract presents a study performed to compare the different methods for formulating a reference load curve for the residential energy consumers. Hypothetically, this reference load curve gives the habitual energy consumption pattern of residential consumer. The aim of creating a reference load curve is to visualize and measure the degree of deviation of consumption load curve from habitual energy consumption load curve of a consumer. The image of reference load curve superposed on consumption load curve is sent to the consumers as part of the feedback, so that they can watch the impact of their efforts as well. For this purpose, certain statistical methods (mean, Kernel Density Distribution) and naïve methods are explored, whereas the advanced methods (RF regression, Neural networks) are in the process of study. The so forth studied methods are analyzed through an indicator that verifies the under-estimation or over-estimation of the reference load curve (to be discussed in detail in the proposed paper).

Scientific Innovation and Relevance

(max 200 words)

Hypothetically, the habitual energy consumption pattern of a residential customer can be visualized in the form of a load curve (hereafter referred as reference load curve) for a standard day. For a particular day, the deviation of consumption load curve from reference load curve gives the measure of the effort made by the residential consumer to implement indirect flexibility. In case of peak shaving, a good effort can be observed if the consumption load curve is under reference load curve. The result should be opposite in the case of load shifting for the period of time to which the load is shifted. For the purpose of experiment, two types of alerts are defined. Orange alert demands the households to implement peak shaving between 6 PM and 8 PM on alert day. Green alert demands the households to implement load shifting from evening to afternoon (between noon and 3 PM). The reference load curve is used to measure the impact of nudge signal on each household for each alert. This in consequence measures the effectiveness of nudge tool to implement indirect energy flexibility in residential sector.

Preliminary Results and Conclusions

(max 200 words)

For half-hourly sampled consumption load curve, one method is to take the mean of historical data for each of the 48 timestamps of day. Another statistical method is to take the peak value of the Kernel density estimation for each of the 48 timestamps of the day. Hypothetically, this peak value is the most probable value of energy consumption for the given half hour timestamp. However, these methods are highly susceptible to season variation and therefore gives less accurate reference load curve.

One naïve method is to take an average of the consumption load curve of day "D-1" with the consumption load curve having maximum energy consumption among the curves of days "D-2" and "D-5" (only weekdays). This reference load curve is used for orange alerts. The vice versa of this method is also formulated for green alerts. Both these reference curve keeps the effect of the near past historical consumption, therefore maintaining the effect of temperature and seasonality. These naive methods are devised to introduce a bias, so that it nudges the households makes a better effort in future. The advanced methods are still in the process of study.

Main References

(max 200 words)

Albadi, M. H., and E. F. El-Saadany. 2007. “Demand Response in Electricity Markets: An Overview.” In 2007 IEEE Power Engineering Society General Meeting, 1–5.

Bivas, Pierre. 2011. “La production d’effacement : comment offrir des économies d’électricité à des millions de foyers.” Le journal de l’ecole de Paris du management n°90 (4): 8–14.

Hatton, Leslie, and Philippe Charpentier. 2014. “Système électrique français : estimation de l’effacement des clients résidentiels,” 14.

Lesgards, Valérie, and Laure Frachet. 2012. “La Gestion de La Demande Résidentielle d’électricité: Retour Sur 30 Ans d’expérimentations Mondiales.” La Gestion de La Demande Résidentielle d’électricité: Retour Sur 30 Ans d’expérimentations Mondiales, no. 607: 162, 164, 192-210 [21 p.].

Neenan, B. 2009. “Residential Electricity Use Feedback: A Research Synthesis and Economic Framework,” 126.

Thaler, Richard H., and Cass R. Sunstein. 2008. Nudge: Improving Decisions about Health, Wealth, and Happiness. Nudge: Improving Decisions about Health, Wealth, and Happiness. New Haven, CT, US: Yale University Press.

 
13:00 - 14:30Session W2.7 (Online Track): Ensuring high quality building simulations
Location: Virtual Meeting Room 1
Session Chair: Charles S Barnaby, CSB Consulting
Virtual Meeting Room 1 
 
13:00 - 13:06

Identifying grey-box models from archetypes of apartment block buildings

Marius Eide Bagle1, Philip Maree2, Harald Taxt Walnum1, Igor Sartori1

1SINTEF Community, Norway; 2SINTEF Digital, Norway

Aim and Approach

(max 200 words)

A potentially large amount of flexibility resides in the space heating of residential buildings. To realize this potential, it is necessary to model heat demand with models that are accurate enough and suitable for real time control.

Well-suited for this purpose are grey-box models, which combine a relatively simple physical descriptions of the building with data-driven inference of key parameters. However, identification of grey-box models poses a challenge: alongside energy use and weather data, the indoor temperature must also be known. Such data are scarcely available. Furthermore, it is not given that measurements from normal operation of buildings provide datasets that are 'rich' enough to successfully drive the identification process, or if special test periods should be carried out. Such a test would require the manipulation of indoor temperatures, possibly in periods of non-occupancy, for several days; a challenging task on real buildings.

This paper presents a method that aims at overcoming this bottleneck by combining features of both white-box and grey-box modelling. A set of white-box models (specifically, IDA-ICE models) representing the Norwegian stock of apartment blocks is available, based on ca. 20 archetypes previously developed in the Tabula/Episcope project [1].

Scientific Innovation and Relevance

(max 200 words)

To enable a large-scale rollout of predictive control systems in the building stock, developing robust methods of model identification is of key importance. Provided that load profiles in the IDA-ICE models are validated (a parallel research activity), it is legitimate to assume that the indoor temperature profiles from the IDA-ICE archetypes are also representative for the real building stock, thus bypassing the need for measurement data.

Under this assumption, the grey-box models are identified from datasets generated by the IDA-ICE archetypes in two modalities: under normal operation with a seasonal (three-month) duration, and under special test periods with a duration of one to two weeks. During the test periods the IDA-ICE archetypes are excited with trains of heating events, Pseudo Random Binary Sequence (PRBS), aiming at exploring a wide and rapidly changing set of indoor temperatures around the comfort zone, ca. between 20 and 24 °C. It is also of interest to investigate the effect of temporal resolution in the identification process.

Preliminary Results and Conclusions

(max 200 words)

Preliminary results have been obtained using the software package CTSM-R [2], which uses an extended Kalman filter (EKF) to formulate a maximum likelihood estimation problem. This is combined with a quasi-Newton method to find the optimal set of parameters. With this setup, there are issues regarding the initial parameterization of the states, which essentially have to be found via a qualified guess. One weakness using the EKF is that it does not incorporate state constraints, nor does it utilize potential underlying non-linear dynamics. To such an extent, Moving Horizon Estimation (MHE) is presented as an alternative optimization-based approach to solving the maximum a-posteriori estimate. Recent advances in computational power makes MHE a viable solution as an asymptotically stable observer which has shown in other cases to provide improved state estimation and greater robustness to poor guesses of the initial state [3].

Results will be evaluated considering both the physical meaningfulness of the parameters, e.g. by ensuring that the energy balance of the model is unbiased [4], and that the parameter values are accompanied by reasonable confidence intervals. To enable a fair comparison between the algorithms, a fixed structure for the grey-box model will be decided a priori.

Main References

(max 200 words)

[1] “Tabula/Episcope - Norwegian archetypes.” [Online]. Available: https://episcope.eu/building-typology/country/no.html. [Accessed: 30-Jun-2020].

[2] H. Madsen et. al, “Continuous Time Stochastic Modeling in R User’s Guide and Reference Manual,” 2018.

[3] Haseltine, Eric L., and James B. Rawlings. "Critical evaluation of extended Kalman filtering and moving-horizon estimation." Industrial & engineering chemistry research 44.8 (2005): 2451-2460.

[4] R. De Coninck, F. Magnusson, J. Åkesson, and L. Helsen, “Toolbox for development and validation of grey-box building models for forecasting and control,” J. Build. Perform. Simul., vol. 9, no. 3, pp. 288–303, 2016.



13:06 - 13:12

Integrating thermal, energy, lighting, and acoustics in building design approach: Lesson learned from students assignments

Rizki A. Mangkuto, Anugrah Sabdono Sudarsono, R.S. Joko Sarwono

Institut Teknologi Bandung, Indonesia

Aim and Approach

(max 200 words)

This paper aims to report results and lesson learned from students assignments in integrating thermal, energy, lighting, and acoustics performance in a building design simulation project. The objectives are to observe the students approach in defining and obtaining the baseline, target, and optimum performance in all mentioned aspects, and to analyse the differences between the submitted design proposals.

The following hypothetical case was assigned to the students: A classroom with two glazed windows is situated on the second floor of a third-story building; the north side is exposed to the exterior, whereas the other three sides are adjacent to an unconditioned corridor. The students were asked to simulate and predict the baseline and target values of thermal, energy, lighting (all using Sefaira) and acoustics (using CATT v8) aspects of the classroom, and optimise them only by modifying the interior material properties. The submitted project reports were analysed statistically to observe the trend.

Scientific Innovation and Relevance

(max 200 words)

An integrated building performance simulation (BPS) approach considering thermal, energy, lighting, and acoustics performance altogether in building design is not so common. Integrating the first three mentioned aspects is indeed popular and is supported by current simulation tools, but the acoustics aspect is often not considered at the same time, i.e. it is not integrated in the design approach. This paper offers an insight on how graduate students (in Building Physics), some of which were professional architect and engineers, integrated and optimised all of those four aspects altogether, in an attempt to modify a classroom using BPS. There are also observations on how the proposed designs are compared to each other.

The results would be of relevance for building practitioners and educators, since the findings suggest that such integrated design can be quite challenging and is not trivial, particularly for those who are not familiar with the integrated approach, despite already having a background in the building industry.

Preliminary Results and Conclusions

(max 200 words)

Based on the submitted reports, it is found that only 50% of the students modified the interior materials by considering the four aspects at the same time, so that the results were optimum for all aspects. The remaining 50% chose to optimise the materials considering the first three aspects, as they could be done in Sefaira, and then modified the material with respect to acoustics aspect in CATT v8; without realising that the last step might also influence or change the thermal, energy, and lighting performance. While this seems like a typical beginner's mistake in BPS, it can also happen for instance to specialists, i.e. those who are experienced BPS users but do not master the four aspects altogether.

Among the aspects, lighting performance (sDA300/50%) is the most consistently predicted, with the coefficient of variance (CV) of 0.16 (baseline) and 0.07 (optimum). In opposite, thermal performance (annual overheating hours) is the least consistent, with CV of 1.68 (baseline) and 1.82 (optimum).

In conclusion, the findings can be applied to improve the content of BPS education by employing integrated building performance design approach.

Main References

(max 200 words)

I. Beausoleil-Morrison (2019) Learning the fundamentals of building

performance simulation through an experiential teaching approach, Journal of Building Performance Simulation, 12:3, 308-325.

P.P. Charles, C.R. Thomas (2009) Four approaches to teaching with building performance simulation tools in undergraduate architecture and engineering education, Journal of Building Performance Simulation, 2:2, 95-114.

E. Mendes, N. Mendes (2019) An instructional design for building

energy simulation e-learning: an interdisciplinary approach, Journal of Building Performance Simulation, 12:3, 326-342.



13:12 - 13:18

Statistical methodologies for verification of building energy performance simulation

Amin Nouri, Jérôme Frisch, Christoph van Treeck

Institute of Energy Efficiency and Sustainable Building (E3D), RWTH Aachen University, Germany

Aim and Approach

(max 200 words)

Building performance simulation tools are being increasingly deployed by researchers and professionals to predict the thermal behavior of buildings. In general, modeling and simulation techniques are employed to determine the thermal characteristics of the building. Validation methods are used to ensure the accuracy of simulation results. Several standardized procedures exist to assess building performance simulation tools, such as ASHRAE Standard 140 as well as the German VDI 6007 and VDI 6020 guidelines. This paper is conducted within a research project funded by the German Federal Ministry for Economic Affairs and Energy (BMWi), which addresses the development of quality standards for building and systems energy performance simulation. The objective of this project is to develop a validation methodology, to define standards for simulation applications and to transfer them into planning practice.

Scientific Innovation and Relevance

(max 200 words)

Buildings account for approximately 40% of the final energy consumption and 36% of the greenhouse gas emissions in Europe (European Commission, 2019). The Paris climate agreement aims to keep the global temperature rise to well below 2 °C above pre-industrial levels and to limit the temperature increase to a maximum of 1.5 °C. In the last few years, building performance simulation tools have been taken into consideration for the scientific community as well as industrial society. However, studies have revealed that there are substantial discrepancies between predictions of building performance simulation tools and the measured energy consumption in practice, which is referred to as the “performance gap”. Validation and verification procedures are essential elements within the development of building simulation tools to assess reliability of the simulation results as well as to find and eliminate eventual bugs in the simulation software.

Preliminary Results and Conclusions

(max 200 words)

The first part of this paper presents the comparison of the different standards and guidelines in the context of building and HVAC system performance simulation. The second part describes a systematic set of test cases for building and HVAC systems based on the ASHRAE Standard 140 and discusses the simulation approach in Modelica/Dymola. The third part presents the development and implementation of a validation methodology, which verifies the plausibility of simulation results and excludes simulation errors to the greatest extent. In this paper, first results as well as comparative analyses will be discussed. Another aspect of the research project is the development of a Platform. The main objective of the Platform is to provide a facility for defining individual test cases, to create individual simulation code, to perform a comparative validation, and to evaluate the accuracy of the simulation tools.

Main References

(max 200 words)

Wetter, M., van Treeck, C. (2017). „IEA EBC Annex 60: New Generation Computing Tools for Building and Community Energy Systems“.

Strachan, P., Svehla, K., Heusler, I., Kersken, M. (2016). „Whole model empirical validation on a full-scale building“. Journal of Building Performance Simulation.

Judkoff, R., Wortman, D., O’Doherty, B., Burch, J. (2008). „A methodology for validating building energy analysis simulations“. NREL, Golden.



13:18 - 13:24

Easy-to-implement simulation strategies for annual glare risk assessment based on the European Daylighting Standard

Bruno Bueno1, Abel Sepúlveda2, Christoph Maurer3, Simon Wacker4, Taoning Wang5, Tilmann E. Kuhn6, Helen Rose Wilson7

1Fraunhofer ISE, Germany; 2Taltech, Estonia; 3Fraunhofer ISE, Germany; 4Fraunhofer ISE, Germany; 5Lawrence Berkeley National Laboratory LBNL, Berkeley CA, USA; 6Fraunhofer ISE, Germany; 7Fraunhofer ISE, Germany

Aim and Approach

(max 200 words)

One of the most important functions of fenestration systems, which triggers user manipulation of the facade, is the protection from daylight glare. The new European daylight standard EN 17037 contains assessment procedures, criteria and information on glare evaluation. Still, mainstream building simulation programs include limited capabilities for glare risk assessment [1], which sometimes results in suboptimal façade design. The problem resides in the complexity and high requirements of state-of-the-art glare evaluation techniques, including those proposed in EN 17037 based on the DGP index [2,3]. In this study, we benchmark available methods for DGP calculation [4,5] and propose simulation strategies that could be easily implemented in simulation programs. This will foster the integration of glare risk assessment in the design process of buildings.

Scientific Innovation and Relevance

(max 200 words)

For a reliable glare risk assessment, it is crucial to account for the direct-direct optical transmittance and cut-off angle of fenestration systems. In this study, we analyse different options to represent the optical behaviour of fenestration components in simulation environments. Bi-directional scattering distribution functions (BSDF) with different resolutions [6] are compared with other strategies such as peak extraction. These representations are based on datasets that have to be experimentally obtained [7] and digitally transferred to simulation environments. The simulation approach, the timestep sampling and the optical representation of the shading technologies determine their applicability in simulation environments and the possibility to be integrated in the design process of buildings.

Preliminary Results and Conclusions

(max 200 words)

In this study, state-of-the-art glare evaluation methods are compared. We propose new strategies based on optical data such as low-resolution BSDF, which is becoming available in international databases, combined with recent approaches such as peak extraction. Efficient sampling strategies reduce the computational cost of dynamic raytracing simulations without loss of accuracy. DGP calculations based on these strategies could be implemented in building simulation environments.

Main References

(max 200 words)

[1] Bueno B, Sepúlveda A. A specific building simulation tool for the design and evaluation of innovative fenestration systems and their control. Building Simulation Conference, Rome, 2-4 September; 2019.

[2] J. Wienold, J. Christoffersen, Evaluation methods and development of a new glare prediction model for daylight environments with the use of CCD cameras, Energy and Buildings (2006).

[3] J. Wienold, T. Iwata, M. Sarey Khanie, E. Erell, E. Kaftan, R.G. Rodriguez, J.A. Yamin Garreton, T. Tzempelikos, I. Konstantzos, J. Christoffersen, T.E. Kuhn, C. Pierson, M. Andersen, Cross-validation and robustness of daylight glare metrics, Lighting Research and Technology (2019).

[4] E.S. Lee, D. Geisler-Moroder, G. Ward, Modeling the direct sun component in buildings using matrix algebraic approaches: Methods and validation, Solar Energy (2018).

[5] M. Abravesh, B. Bueno, S. Heidari, T.E. Kuhn, A method to evaluate glare risk from operable fenestration systems throughout a year, Building and Environment (2019).

[6] G. Ward, M. Kurt, N. Bonneel. Reducing anisotropic BSDF measurement to common practice. In: Proceedings of the Eurographics 2014 Workshop on Material Appearance Modeling: Issues and Acquisition. Lyon, France: Eurographics Association; 2014, p. 5–8.

[7] P. Apian-Bennewitz. New scanning gonio-photometer for extended BRTF measurements. In: Proceedings of SPIE; 2010.



13:24 - 13:30

A machine-learning framework for daylight and visual comfort assessment in early design stages

Hanieh Nourkojouri1, Zahra Sadat Zomorodian1, Mohammad Tahsildoost1, Zohreh Shaghaghian2

1Shahid Beheshti University, Iran, Islamic Republic of; 2Texas A&M University, College Station, United States

Aim and Approach

(max 200 words)

This research is mainly focused on daylight assessment in early stages of design through a new framework which is based on machine learning algorithms. A dataset was primarily developed from 2880 simulations derived from Honeybee for Grasshopper. The simulations were done for a shoebox space with a one side window. The alternatives emerged from different physical features including room dimensions, interior surfaces reflectance, window dimensions and orientations, number of windows and shading states. The metrics used for daylight evaluations included UDI, sDA, mDA, ASE and sVD. Quality Views were analyzed for the same shoebox spaces via a grasshopper-based algorithm which was developed from the LEED v4 evaluation framework for Quality Views. The dataset which had finally daylight, visual comfort and quality views outputs indices was further analyzed with Artificial Neural Network algorithm written in Python. The developed model could be used in early design stages analyzes without the need for time consuming simulations in previously used platforms and programs.

Scientific Innovation and Relevance

(max 200 words)

This work presents a concept for development of a new method to evaluate daylight assessment and views at the same time without the need for time conserving simulations. The mentioned method includes 5 indices for daylight and visual comfort evaluations and 2 indices for evaluation of quality views. Having all these 7 metrics together could give the designers a comprehensive vision for the designed space’s performance in daylight and visual comfort. Furthermore, with the application of machine learning algorithms like ANN which is used in this research, these results could be delivered to the designers and stakeholders quickly with determination of some simple physical features of the designed spaces and there will be no need for vast knowledge in building physics modeling and simulations for architects and designers using them.

Preliminary Results and Conclusions

(max 200 words)

In this research a model was developed for prediction of daylight, visual comfort and quality view assessment at the same time in a space. The model takes some simple physical features of the space as inputs and the estimated outputs include 7 metrics indicating the daylight and visual comfort performance of the defined space. The model is based on an optimized ANN algorithm which achieved a prediction accuracy of about 97% and MSE index of 0.002.

Main References

(max 200 words)

Ayoub, M., 2020. A review on machine learning algorithms to predict daylighting inside buildings, Solar Energy, Vol 202, p249-275.

Mardaljevic, J., 2015. Climate-based daylight modelling and its discontents. Presented at the Simple Buildings Better Buildings? Delivering performance through engineered solutions, CIBSE Technical Symposium,London, April 16-17th

Ngarambe, J., Irakoze, A., Young Yun, G., Kim, G., 2020, Comparative performance of machine learning algorithms in prediction of indoor daylight illuminances, Sustainability 2020,12(11), 4471

Tregenza, P., Mardaljevic, P., 2017, Daylighting Buildings: Standards and the needs of designer, Lighting Research and Technology, Vol 50, p63-79.

LEED® green building program, v4 for Building design and construction.



13:30 - 13:36

Reducing heat island effect: a mathematical model of green roof design

Jing Hong1, Dennis Michael Utzinger2

1Rivion; 2University of Wisconsin- Milwaukee

Aim and Approach

(max 200 words)

Green roofs ease the heat island effect. Optimizing green roof design helps achieve this goal more efficiently. This paper proposes an energy model of green roofs to estimate surface temperature and validates them with experimental evidence that measured on the green roof at the University of Wisconsin - Milwaukee. Two energy balance equations separately indicate the heat flux through the bare soil and vegetation-covered surfaces. The energy flux density and surface temperature of bare soil and vegetation-covered surface were modeled by the proposed mathematical models. In the meantime, the effects of color, soil depth, and plant type on the surface temperature were analyzed to conclude the optimal green roof design.

Scientific Innovation and Relevance

(max 200 words)

In the proposed energy model, the calculation of radiation, convection, and evaporation on surface temperature is simplified to use fewer unknown variables. For that reason, this model only requires basic weather data and an initial soil temperature reading to estimate the green roof surface temperature in any equation-solving program.

Preliminary Results and Conclusions

(max 200 words)

The energy balance models explain how surface color, soil depth, and plant types affect the surface temperature of a green roof. In conclusion, the green roof surface temperature can be reduced by lighter surface color, shallower soil depth, and plants with lower internal leaf resistance and larger leaf size.

Main References

(max 200 words)

[1] Susca, Tiziana, Stuart R. Gaffin, and G. R. Dell’Osso. "Positive effects of vegetation: Urban heat island and green roofs." Environmental pollution 159, no. 8-9 (2011): 2119-2126.

[2] Sailor, David J. "A green roof model for building energy simulation programs." Energy and buildings 40, no. 8 (2008): 1466-1478.

[3] Duffie, John A., and William A. Beckman. Solar engineering of thermal processes. John Wiley & Sons, 2013.

[4] Berdahl, Paul, and Marlo Martin. "Emissivity of clear skies." Solar Energy 32, no. 5 (1984): 663-664.

[5] Watmuff, J. H., W. W. S. Charters, and D. Proctor. "Solar and wind induced external coefficients-solar collectors." Cooperation Mediterraneenne pour l'Energie Solaire (1977): 56.

[6] Farouki, Omar T. Thermal properties of soils. No. CRREL-MONO-81-1. Cold Regions Research and Engineering Lab, Hanover NH, 1981.

[7] Oke, Timothy R. Boundary layer climates. Routledge, 2002.

[8] Gates, David M. Biophysical ecology. Courier Corporation, 2012.

[9] Monteith, John, and Mike Unsworth. Principles of environmental physics: plants, animals, and the atmosphere. Academic Press, 2013.

[10] American Society of Heating, Refrigerating and Air-Conditioning Engineers. 2013 Ashrae Handbook: Fundamentals. Inch-pound ed. Atlanta, Ga.: Ashrae, 2013

[11] Oyj, Vaisala. "Humidity Conversion Formulas—Calculation formulas for humidity." Vaisala: Helsinki, Finland (2013).



13:36 - 13:42

Semantic web ontologies for buildings objects and their performance data

Eleanna Panagoulia, Zachary Lancaster, Tarek Rakha

Georgia Institute of Technology, United States of America

Aim and Approach

(max 200 words)

The normative ontologies of tools, federated and tailored by the Architecture, Engineering, Construction and Operations industry (AECO), constrain collaboration and interoperability due to the creation of specific and bounded representational spaces, outside of which, software cannot operate. Although Building Information Modeling (BIM) provides a foundation for collaboration and data exchange within a common platform, professional practice still relies heavily on document sharing to circumvent the limits of proprietary software ontologies, especially when integrating performance analytics.

Current approaches of using monolithic data schemas to communicate information (i.e. IFC) constrain the domain of possible content, hence reducing the data expressivity and failing to capture the diversity of data in the built environment. To overcome this constraint we must provide access to information across platforms without presupposing information loss. This requires a modular, consistent, specific enough vocabulary, to describe any element, without at the same time being ambiguous.

This paper proposes one such vocabulary in the form of a semantic web-based ontology for representing building envelopes and their linked data. We demonstrate the use of this ontology in a platform agnostic exchange between envelope performance analysis and industry standard design software; enabling decision-making for building envelopes in the context of high-performance retrofitting design.

Scientific Innovation and Relevance

(max 200 words)

The ability to represent building elements as semantically complete objects would contribute to higher performance architectures. However, the identification and classification of building objects depends largely on user interpretation and appears to operate without an explicitly documented or comprehensive ontology. This impedes the consistent linking of analytical outcomes and auxiliary data to envelope systems and prevents the creation of a common information repository. This lack of consistent understanding of a project, across all disciplines, results in miscommunication and thus, deviation between the actual and anticipated performance.

Previous research indicated that a single interface would be insufficient to handle the multifarious datasets associated with the building objects and their performance. This paper’s innovation is in the employment of a semantic web approach that proposes the use of consistent and practical ontologies describing both building elements and building performance data, while also describing the relationship between building elements and their analytical data. This ontological definition focuses on a bi-directional exchange between platforms, and makes performance and simulation data available to practitioners.

Preliminary Results and Conclusions

(max 200 words)

This research specifies two novel ontological definitions and a software interface that makes use of these definitions. The first one is defined as the Ontology for Building Objects (OBO), describes an explicit graph-based, rule-driven description of building envelopes as discrete elements and the relationships between them. While OBE focuses primarily on a description of geometric objects, the second, the Ontology for Building Performance Data (OBPD), is a minimal definition for building performance analytics, its data requirements, outputs and the relationship between an analysis and a building element or set of elements. While OBO is strongly aligned with OBPD, it is also aligned with other known building ontologies.

The paper showcases an application that operates as middleware between different data stores, the user and an interface for data serialization towards a common data environment. We demonstrate the above using Revit’s API and a dataset common to energy audits of existing buildings. The result is an automated method of identifying components enabled by the OBO’s building objects definition and linking them to performance analytics based on OBPD’s relationship specification. We present a lossless exchange and mapping of data that provides the ability to represent non-native, analytical data directly in the BIM environment.

Main References

(max 200 words)

[1] R. Volk, J. Stengel, and F. Schultmann, “Building Information Modeling (BIM) for existing buildings - Literature review and future needs,” Automation in Construction. 2014.

[2] E. Kamel and A. M. Memari, “Review of BIM’s application in energy simulation: Tools, issues, and solutions,” Autom. Constr., vol. 97, no. October 2018, pp. 164–180, 2019.

[3] P. Pauwels, M. Poveda-Villalón, Á. Sicilia, and J. Euzenat, “Semantic technologies and interoperability in the built environment,” Semant. Web, 2018.

[4] U. Knaack, “Potential for innovative massive building envelope systems – Scenario development towards integrated active systems,” J. Facade Des. Eng., 2015.

[5] S. B. Sadineni, S. Madala, and R. F. Boehm, “Passive building energy savings: A review of building envelope components,” Renew. Sustain. Energy Rev., 2011.

[6] A. Mahdavi and D. Wolosiuk, “A Building Performance Indicator Ontology : Structure and Applications”, 2019.

[7] M. H. Rasmussen, M. Lefrançois, P. Pauwels, C. A. Hviid, and J. Karlshøj, “Managing interrelated project information in AEC Knowledge Graphs,” Autom. Constr., 2019.

[8] M. Bonduel, M. Vergauwen, R. Klein, M. H. Rasmussen, and P. Pauwels, “A novel workflow to combine bim and linked data for existing buildings,” eWork Ebus. Archit. Eng. Constr. - Proc. 12th Eur. Conf. Prod. Process Model. ECPPM 2018.



13:42 - 13:48

A machine-learning framework for acoustic design assessment in early design stages

Reyhane Abarghooie1, ZahraSadat Zomorodian1, Mohammad Tahsildoost1, Zohreh Shaghaghian2

1Shahid Beheshti University, Tehran, Iran; 2Texas A&M University, College Station, United States

Aim and Approach

(max 200 words)

Predicting acoustic performance by utilizing simulation tools is a widely used approach being favored over time-costly scale model studies. In this field, building acoustic simulation tools are complicated by several challenges, including the high cost of acoustic tools, the need of acoustic expertise, and the time-consuming process of acoustic simulation. This research presents a methodology for measuring acoustic comfort using a soft-sensing approach in the early design stages of the building. This work presents a proof of concept for a novel machine learning method to estimate a set of typical room acoustics parameters by using only geometrical information as input features.

The proposed model is trained and evaluated by using a novel dataset composed of acoustical simulation of a single room with 2916 different configurations. In the stimulation process features that include room dimensions, window size, material absorption coefficient, furniture, and shading type has been analyzed by using Pachyderm acoustic software. The mentioned dataset is used as the input of a machine-learning model based on Deep Neural Network (DNN). The machine learning model is fully-connected DNN with 5 hidden layers.

Scientific Innovation and Relevance

(max 200 words)

Acoustic comfort is one of the most important design parameters that affect people's satisfaction and productivity. Therefore predicting the sound conditions in the building is noticeable in both the research and the industrial environments. Traditional methods to study the sound propagation inside the rooms can be divided into three approaches: the geometrical models, the wave-based models, and the statistical models. The parameter values that render the acoustical comfort of a room should be estimated based on the geometry of the virtual room. While the complete physical models are typically computationally too demanding, an approximation can be made by using simplified mathematical methods such as Sabin or Eyring. Formulas that can only calculate RT, and do not often hold in typical environments such as offices, schools, accommodations, commercial, and healthcare environments. In this way, we aim to estimate some of the acoustical indexes which, include Reverberation Time (RT), Early Decay Time (EDT), Speech Transmission Index (STI), Clarity (C80), and Definition (D50), where the estimated values should be accurate enough for the plausible rendering of acoustic virtual reality. The goal of this project is to introduce a model with short calculation time to estimate the mentioned indexes in the nominated spaces.

Preliminary Results and Conclusions

(max 200 words)

This work presents a machine-learning-based method to estimate the room acoustic indexes. The model takes geometric and physical features of a room as input and output the estimated RT, EDT, STI, C80, and D50 indexes values as a function of frequency. All models were trained and evaluated in a dataset that contains parametric acoustic simulation.

The estimation was performed by using a machine-learning model based on a DNN. The baseline model achieves appropriate results by using geometrical features extracted from the 3D model of rooms. The stimulation model achieves a prediction accuracy of approximately more than 96% during the mentioned indexes.

Main References

(max 200 words)

Rossing, T.D. (2014). Springer Handbook of Acoustics. New York, Ny Springer.

Falcón Pérez (2018). Machine-learning-based estimation of room acoustic parameters. Master’s thesis. Aalto University, Espoo

J. Bianco, M., Gerstoft, P., Traer, J., Ozanich, E., A. Roch, M., Gannot, S. and Alban Deledalle, C. (2019). Machine learning in acoustics: Theory and applications. The journal of the acoustical society of America.

H. and Zhai, Z. (John) (2016). Advances in building simulation and computational techniques: A review between 1987 and 2014. Energy and Buildings, 128, pp.319–335.

Huang, B., Pan, Z., Liu, Z., Hou, G. and Yang, H. (2017). Acoustic amenity analysis for high-rise building along urban expressway: Modeling traffic noise vertical propagation using neural networks. Transportation Research Part D: Transport and Environment, 53, pp.63–77.

Lovedee-Turner, M. and Murphy, D. (2018). Application of Machine Learning for the Spatial Analysis of Binaural Room Impulse Responses. Applied Sciences, 8(1), p.105.



13:48 - 13:54

A Python library for Radiance matrix-based simulation control and EnergyPlus integration

Taoning Wang1, Greg Ward2, Eleanor S. Lee1

1Lawrence Berkeley National Lab, United States of America; 2Anyhere Software

Aim and Approach

(max 200 words)

In the realm of building simulation, there are many reasons why accurate, efficient ray-tracing-based solar radiation and daylighting simulations are needed: 1) accurate thermal and visual comfort predictions rely on detailed maps of solar radiation and luminance on an occupant’s body or field of view. 2) broader adoption of energy efficiency, indoor environmental quality, and healthy building standards require accurate modeling of innovative fenestration solutions, and 3) increased trends toward integrated, advanced building design and control solutions require efficient models to work seamlessly within co-simulation environments, such as Spawn-of-EnergyPlus. Radiance matrix-based simulation methods provide efficient and accurate ways to simulate annual/dynamic daylighting and solar radiation, particularly optically-complex operable shades, and dynamic glazings. However, real-world adoption could be more pervasive if the model setup and simulation workflow were not so difficult to learn and prone to user errors.

The goal of this work is to enable users and software developers to adopt advanced Radiance matrix-based simulation methods without extensive knowledge and experience. A Python-based open-source library frads was developed, along with a series of command-line programs, to automate and speed up the use of these advanced simulation methods.

Scientific Innovation and Relevance

(max 200 words)

Ray-tracing algorithms have typically been too time-consuming for practical use in annual simulations. With matrix-based methods, the time needed to conduct annual simulations using ray-tracing tools has been reduced by several orders of magnitude. With the advent of version 9.3, EnergyPlus has exposed its core simulation engine to any external software environment, which enables runtime Radiance and EnergyPlus integration. The entire workflow is implemented as a command-line program, but software developers can use frads to incorporate the workflow into any third-party software.

frads consist of many standard Radiance operations allowing for automated model translation from EnergyPlus, matrices generation, and runtime data-exchange with EnergyPlus. frads also comes with several command-line programs for routine operations, and these programs also serve as examples of using the frads library. The chief among these programs is mrad, an executive program that automates the Radiance two- to six-phase simulation workflow. Users need to provide the model description (e.g., geometry, material, and location) and parts of the model that are parametrized. mrad will then choose the suitable matrix phase method based on user-specified speed and accuracy requirements and carry out matrix generation and multiplication workflow, outputting irradiance, illuminance or luminance results per time step.

Preliminary Results and Conclusions

(max 200 words)

The framework for frads has been developed with further refinements currently underway. Early tests indicate that Radiance and EnergyPlus run-time integration requires minimal to no user intervention, enabling rapid widespread adoption. One of the key advantages of run-time data-exchange between Radiance and EnergyPlus is that it enables the evaluation of advanced model predictive control of building dynamic facade in a multizone building. During runtime, at each timestep, EnergyPlus simulation pauses; given a dynamic facade control signal (e.g., via Spawn/ Modelica or manufacturer component model), Radiance computes resulting facade energy transfer data, which are then used in EnergyPlus to complete the relevant heat balance calculations.

With these accurate simulation methods as part of the toolset, engineers and designers are able to differentiate facade product performance through simulation, which in turn spurs innovations from inventors and manufacturers. Integration of Radiance and EnergyPlus in a co-simulation environment further boosts the confidence among engineers and designers in the whole-building energy simulation results.

Main References

(max 200 words)

Gehbauer, C., Blum, D. H., Wang, T., & Lee, E. S. (2020). An assessment of the load modifying potential of model predictive controlled dynamic facades within the California context. Energy and Buildings, 210, 109762.

Wang, T., Ward, G., & Lee, E. S. (2018). Efficient modeling of optically-complex, non-coplanar exterior shading: Validation of matrix algebraic methods. Energy and Buildings, 174, 464-483.

Lee, E. S., Geisler-Moroder, D., & Ward, G. (2018). Validation of the Five-Phase Method for Simulating Complex Fenestration Systems with Radiance against Field Measurements.

McNeil, A., & Lee, E. S. (2013). A validation of the Radiance three-phase simulation method for modelling annual daylight performance of optically complex fenestration systems. Journal of Building Performance Simulation, 6(1), 24-37.



13:54 - 14:00

Functional mock-up unit based generic threat injection framework for energy efficient and resilient buildings

Yangyang Fu, Xing Lu, Zheng O'Neill

Texas A$M University, United States of America

Aim and Approach

(max 200 words)

Fault detection and diagnosis in building energy and control systems relies much on accessible faulty data, which can be obtained from experiments or dynamic simulation. While experiments that inject faults to actual building energy and control systems are risky to building operators, high-fidelity dynamic modeling and simulation can provide flexibility of injecting all types of faults to the system in order to investigate their impact.

EnergyPlus as a popular building energy simulator has integrated plenty of faulty models. However, the development exposed several limitations. First, it is difficult to model control-related faults, such as inappropriate PID parameters and communication delays etc. Second, the injection of pressure-involved faults is not straightforward. For example, to model duct fouling, users need to adjust the pressure head, minimum and maximum air flowrate in the fan model. Third, faults cannot be injected in the middle of simulation. Forth, fault evolution patterns are not considered.

This paper presents a flexible FMU-based fault injection framework that can address the above-mentioned issues. This framework will consider a comprehensive list of typical faults in the HVAC system. The injection method will be mathematically presented. Component-level and system-level faulty modeling and simulation will be demonstrated in the case study.

Scientific Innovation and Relevance

(max 200 words)

This paper presents a flexible and generic functional mock-up unit (FMU) based threat injection frame- work in Python. FMU is a simulation model that is compliant to the functional mock-up interface (FMI), which defines a standardized interface for a model so that such a model can be simulated in a different en- vironment for model exchange or co-simulation. The utilization of FMU in this paper is to provide a standardized model interface for different building energy simulators so that a generic threat library can be connected to it and perform threat evaluation. The proposed framework can address most of the identified research gaps in terms of threat modeling and simulation. Currently, EnergyPlus, TRNSYS and Modelica models can all be compiled to FMU models. Therefore, this proposed framework can be reused for all three simulators with minimum modifications when the different software structures of these three simulators should be taken into considerations.

Preliminary Results and Conclusions

(max 200 words)

This paper presents a generic and flexible threat in- jection framework based on Functional Mock-up Unit (FMU). Several Python libraries are developed to address automating the generation of FMU wrap- per models, define threats and threat injection, and perform step-wise simulation for both baseline and threat-injected systems. The standalone definition of threats and the use of FMU as modeling base enables this framework to be easily expanded to other FMU- supported building energy simulators. The framework is demonstrated in a Modelica/FMU environment by modeling and simulating single-/multiple- order of threats. The simulation results show that the framework can provide flexibility of injecting different types of threats at different starting time for different duration.

Main References

(max 200 words)

Kim, Janghyun, Stephen Frank, James E. Braun, and David Goldwasser. "Representing small commercial building faults in EnergyPlus, Part I: Model development." Buildings 9, no. 11 (2019): 233.

Kim, Janghyun, Stephen Frank, Piljae Im, James E. Braun, David Goldwasser, and Matt Leach. "Representing Small Commercial Building Faults in EnergyPlus, Part II: Model Validation." Buildings 9, no. 12 (2019): 239.

Granderson, Jessica, Guanjing Lin, Ari Harding, Piljae Im, and Yan Chen. "Building fault detection data to aid diagnostic algorithm creation and performance testing." Scientific data 7, no. 1 (2020): 1-14.

Li, Yanfei, and Zheng O’Neill. "A critical review of fault modeling of HVAC systems in buildings." In Building Simulation, vol. 11, no. 5, pp. 953-975. Tsinghua University Press, 2018.

Zhang, Rongpeng, and Tianzhen Hong. "Modeling of HVAC operational faults in building performance simulation." Applied Energy 202 (2017): 178-188.



14:00 - 14:06

Real-time light simulation methodology for expedited comparison and optimization studies through agent-based photon modeling

Vishal Vaidhyanathan, Jichen Wang

Carnegie Mellon University, United States of America

Aim and Approach

(max 200 words)

Daylight Simulations for illumination analyses for tasks involving comparative evaluation and optimization are time taking due to their dependency on external simulation engines. Conventional daylight analysis workflows for quantitative analysis in early phase design decisions for multiple design iterations can be cumbersome and require running thousands of test cases to optimize a workspace for point in time illuminance. This research proposes a methodology for utilizing light simulation as a metric for optimization that uses agent based modelling of photon particles, mimicking their properties using certain policies to generate instantaneous daylight illumination results for comparative and qualitative analysis of architectural spaces. This algorithm removes external dependencies of simulation engines and runs on the CPU. Since it works with direct geometry collision and particle based methods, it works with non-orthogonal and non-linear geometries as well at real-time. A large analysis test mesh can also be executed in real time using multi-threading of particle groups. This enables quick performance optimization for real time design decision making. It also consists of a front end interface for non-intuitive users to perform comparative studies with ease where fitness graphs are visualized in real time.

Scientific Innovation and Relevance

(max 200 words)

Daylight simulations for tasks involving comparative evaluation, optimization, etc. - are time taking. They require external simulation-engine dependencies and take a while to return results. While the required tasks are comparative in nature, and multiple design options are to be rapidly evaluated and ranked, the performance evaluation process must be expedited (almost real-time), easy to setup (non-intuitive) and computationally non-intensive. In such scenarios, it is also sufficient if results are not absolute but rather comparative and “rankable”. Agent Based Modelling (ABMs) is an approach to model systems composed of autonomous and interacting agents that have a set of policies or behavioral rules and are constrained in an environment. Parallels can be drawn between ABM and the properties of light particles (Photons). This research project explores if ABM can be used to emulate light behavior to an extent that it is possible to compare multiple design options and make daylight performance directed design decisions, in an expedited way and in real-time. The amount of illuminance and its uniformity are the two most critical criteria to validate good lighting conditions and are thus evaluated in this tool. The main inputs for this tool are the sun angle and geometry surfaces.

Preliminary Results and Conclusions

(max 200 words)

This methodology with light simulation and optimization is flexible and extremely user friendly where input parameters can be changed during the design process that gives quantifiable standards for comparing design options. The tool gives the designer the power to come up with design choices by themselves, where the evaluation tool is just a helper for decision making. By alternating the input parameters and the definition of geometries, it can also be applied in other kinds of design processes. With this agent based algorithm, one can simulate the light behavior with a rough accuracy and fast calculation. Given that there are already plenty of well established light simulation tools in the field, a comparison was made between this tool and ladybug for grasshopper. The results though not as accurate as ladybug, resulted in the run time being very short which was almost comparable to a real time calculation. Moreover the input settings are much simpler than other tools given that it can take any surface type objects as the geometry input. These benefits make this simulator a very good tool in daylight evaluation and optimization by exploring a large amount of possibilities with multiple geometrical inputs to find the optimized solution.

Main References

(max 200 words)

1. Illuminating Engineering Society. IES Approved Method: Spatial Daylight Autonomy (sDA) and Annual Sunlight Exposure (ASE). New York: IES; 2012. (IES LM-83-12).

2. Chamilothori, Kynthia & Chinazzo, Giorgia & Rodrigues, João & Dan-Glauser, Elise & Wienold, Jan

& Andersen, Marilyne. (2019). Subjective and physiological responses to façade and sunlight pattern

3. United States Green Building Council (USGBC), retrieved 2020.



14:06 - 14:12

Radiant spectral energy for simulation in the built environment

Joseph Del Rocco, Joseph T. Kider Jr.

University of Central Florida, School of Modeling, Simulation, and Training

Aim and Approach

(max 200 words)

Fast and accurate daylighting and energy performance simulations are crucial for real-time control systems (RCS) in the built environment. RCS include responsive facades, adaptive e-glass, and smart HVAC control systems. State-of-the-art building monitoring systems driving the RCS require spectral energy inputs to take full advantage of both light and heat of solar and sky radiation. Additionally, building designers also require spectral energy for building and fenestration design and material decisions relating to circadian rhythm daylighting. Unfortunately, modern daylighting and energy simulations often neglect spectral energy in efforts to reduce computation time, and therefore do not provide the full global-illumination and energy solution needed by fine-grained RCS. We present an accurate, interactive, physically-based approach that utilizes a Transition Portal radiosity engine (Kider et al., 2019) to compute a full global-illumination solution with spectral energy for building simulations in real-time. This approach allows building simulations to leverage the visible spectrum for more accurate daylighting and the full spectrum for energy analysis. This novel method is intended for real-time control systems in the built environment and building adaptation for circadian daylighting.

Scientific Innovation and Relevance

(max 200 words)

Modern building performance simulation often ignores real-time spectral energy input for various reasons. The calculations can be time-consuming and the data needs to be transformed and marshaled through a diverse array of legacy and modern daylighting and energy software systems (modeling packages, fenestration software, OpenStudio, EnergyPlus, Radiance, etc.). However, daylighting and energy performance software must eventually use full-spectrum solar and sky radiation to provide the most accurate results. Doing so may even help to simplify the building performance pipeline. We have anticipated this and progressively worked towards a solution for fine-grained real-time control systems manipulating both light and heat from the same spectral inputs. We have developed a novel system that interfaces with our radiosity engine which processes the spectral inputs and produces spectral outputs and can interface with modern tools. Spectral energy is generated from sky conditions through a machine-learned model (Del Rocco, 2020) from both real-world skydome photographs and synthetic sky renders to demonstrate our system under varied times of day and sky conditions. We also propose and simulate a novel adaptive e-glass solution that filters heat during warm climates but allows it during cool climates, to maximize energy performance with natural heating.

Preliminary Results and Conclusions

(max 200 words)

We performed daylighting simulations and energy analysis on three separate building spaces with the following real-time control systems: automated blinds, a kinetic facade, and various e-glass configurations. Our preliminary results show that our spectral energy system is definitely fast enough to be used by building monitoring systems to drive real-time control systems, as well as by building designers using parametric design to plan shading devices and materials. We also demonstrate that our proposed adaptive e-glass solution can properly filter heat energy from the upper spectra during warm climates (allowing it during cool climates) based on configured limits, contributing to an overall more energy-efficient building performance solution. A cyber-physical prototype building monitoring system with e-glass control is proposed, which monitors the skydome with an all-sky camera as the root input of spectral energy, and then simulates the propagation of the spectral energy input throughout the building efficiently. These experiments demonstrate the feasibility of a system that can handle spectral energy calculations for building performance simulations and control systems in real-time.

Main References

(max 200 words)

Kider, J. T., Walter, B., Fang, S., Sekkin, E., & Greenberg, D. P. (2019). Transition Portal for daylighting calculations in early phase design. Energy and Buildings.

Del Rocco, J., Bourke, P. D., Patterson, C. B., & Kider, J. T. (2020). Real-time spectral radiance estimation of hemispherical clear skies with machine learned regression models. Solar Energy.

S. F. Rockcastle, M. Danell, L. Petterson, and M. L. Ámundadóttir (2020). The Impact of Behavior on Healthy Circadian Light Exposure Under Daylight and Electric Lighting Scenarios. ACEEE Summer Study on Energy Efficiency in Buildings 2020.

Balakrishnan, P., & Jakubiec, J. A. (2019). Spectral Rendering with Daylight: A Comparison of Two Spectral Daylight Simulation Platforms. IBPSA Conference.

Rockcastle, S., Ámundadóttir, M. L., & Andersen, M. (2019). The Case for Occupant-Centric Daylight Analytics: a Comparison of Horizontal Illumination and Immersive View.International Conference of the International Building Performance Simulation Association

Adaptive Lighting for Alertness (ALFA) Software. https://solemma.com/Alfa.html

Inanici, M., and ZGF Architects LLP (2015). LARK Spectral Lighting plugin to Grasshopper. https://faculty.washington.edu/inanici/Lark/Lark_home_page.html

Ward, G. J. (1994, July). The RADIANCE lighting simulation and rendering system. In Proceedings of the 21st annual conference on Computer graphics and interactive techniques.



14:12 - 14:18

Short-term forecasting of building energy consumption with deep generative learning

Yichuan X. Ma

The University of Hong Kong, Hong Kong S.A.R. (China)

Aim and Approach

(max 200 words)

Short-term building energy consumption forecasting is highly valuable from both a technical and an economic point of view. In this paper, a deep generative learning model (GAN-Plus) taking account of short-term future meteorological data is proposed to accurately forecast building energy consumption in the near future. A conventional machine learning model (multilayer perceptron, MLP) and a non-meteorology-based version of the proposed model (GAN-Zero) were developed and comparatively tested as baseline models. Multi-year hourly meteorological data and actual energy consumption measurements from two office buildings in Shanghai were used for modelling and testing.

Scientific Innovation and Relevance

(max 200 words)

(1) A novel generative short-term forecasting framework was delineated.

(2) Customised conditional GAN-based model with a 1D-UNet generator under the generative short-term forecasting framework were developed and quantitatively evaluated under multiple granularity settings.

(3) Historical and future meteorological information was taken into consideration to improve forecasting accuracy.

(4) Cross-case generalisability, which is an underappreciated issue in the field of building energy forecasting, was discussed.

Preliminary Results and Conclusions

(max 200 words)

State-of-the-art accuracy and decent cross-case generalisability of the proposed GAN-based models were demonstrated. The proposed model outperformed the chance level and all the baseline models, achieving accuracies of 85.48% with hourly granularity and 94.77% with daily granularity. MLP failed in the cross-case forecasting task with an hourly CV-RMSE notably larger than 30%. Though similar in terms of performance in hourly forecasting, GAN-Plus showed superior accuracy (with a difference > 1%) than GAN-Zero in daily forecasting. In the noise robustness analysis, GAN-Plus demonstrated strong capability in dealing with the uncertainties in the future meteorological clues, with less than 1.5% deterioration of accuracy with a noise level of 20%. The advantage and potential risks of using the proposed GAN-Plus model were further discussed.

Main References

(max 200 words)

[1] Deb, C., F. Zhang, J. Yang, S. E. Lee and K. W. Shah (2017). "A review on time series forecasting techniques for building energy consumption." Renewable and Sustainable Energy Reviews 74: 902-924.

[2] Fan, C., Y. Sun, Y. Zhao, M. Song and J. Wang (2019). "Deep learning-based feature engineering methods for improved building energy prediction." Applied energy 240: 35-45.

[3] Goodfellow, I. J., J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville and Y. Bengio (2014). "Generative adversarial networks." arXiv preprint arXiv:1406.2661.

[4] Ma, Y. X. and C. Yu (2020). "Impact of meteorological factors on high-rise office building energy consumption in Hong Kong: From a spatiotemporal perspective." Energy and Buildings 228: 110468.

[5] Mirza, M. and S. Osindero (2014). "Conditional generative adversarial nets." arXiv preprint arXiv:1411.1784.

[6] Monfet, D. and P. Radu Zmeureanu PhD (2009). "Calibration of a building energy model using measured data." ASHRAE Transactions 115: 348.

Ronneberger, O., P. Fischer and T. Brox (2015). U-net: Convolutional networks for biomedical image segmentation. International Conference on Medical image computing and computer-assisted intervention, Springer.

 
13:00 - 14:30Session W2.8 (Online Track): Buildings paving the way for the energy transition
Location: Virtual Meeting Room 2
Session Chair: Lori Barbara McElroy, University of Strathclyde
Virtual Meeting Room 2 
 
13:00 - 13:06

Economic and emission reduction potential of renewable based energy systems in an apartment building in cold climatic conditions

Hassam ur Rehman, Ala Hasan, Francesco Reda

VTT Technical Research Centre of Finland, Finland

Aim and Approach

(max 200 words)

Climate change is one of the biggest challenges, largely caused by emissions, and to address such issue, renewable energy can be used for buildings and districts energy demands. The aim is to design and simulate a novel renewable based energy system integrated with the buildings in the district and to compared the proposed system against the reference energy system. The energy system is designed to provide space heating, domestic hot water and electricity to the buildings in the community. TRNSYS dynamic simulation software is used to model the energy system. Costs and CO2 emission are calculated and compared for the novel renewable based energy system and reference energy system.

Scientific Innovation and Relevance

(max 200 words)

The cities and districts are setting ambitious targets to make buildings and districts carbon neutral in an economical manner. The novelty is to design renewable energy based district heating system with storage in order to integrate buildings in the community with clean energy production source. The focus and novelty lies in the analysis of the CO2 reduction potential, rather then technical performance. In addition to this the emission reduction cost and relative emission reduction is compared to the reference district heating system, to show the benefits. The concept is proposed in order to reduce the CO2 emissions to reach the European Commission and cities targets of 2050.

Preliminary Results and Conclusions

(max 200 words)

The renewable energy based energy system can provide energy to the buildings in the community. These systems have the potential to reduce the CO2 emissions from the present state-of-the-art district heating girds by more then 50%. The onsite energy fraction can vary between 1% to 97%. The emission reduction cost can vary between 2 €/kg CO2/yr to 6 €/kg CO2/yr. Such renewable based systems could lower the carbon dioxide emissions from the existing energy systems to meet the Europe emissions reduction and cities targets.

Main References

(max 200 words)

[1] ur Rehman, Hassam, et al. "Towards positive energy communities at high latitudes." Energy conversion and management 196 (2019): 175-195.

[2] Hirvonen, Janne, et al. "Towards the EU emissions targets of 2050: optimal energy renovation measures of Finnish apartment buildings." International Journal of Sustainable Energy 38.7 (2019): 649-672.



13:06 - 13:12

Integration of a flexible tensile material in a second skin façade system: a passive method to enhance the energy performances of the Italian building scenario

Giovanni Ciampi, Yorgos Spanodimitriou, Michelangelo Scorpio, Antonio Rosato, Sergio Sibilio

Department of Architecture and Industrial Design, University of Campania Luigi Vanvitelli, Italy

Aim and Approach

(max 200 words)

In Italy the building panorama is mostly represented by historical buildings or buildings built in the mid-twentieth century, when the performances of the building envelope were scarcely considered [1]. Thus, in order to provide a comfortable indoor space for occupants, a considerable amount of energy is consumed, especially for the heating and cooling. For these reasons, retrofit actions are continuously fostered by the government, in order to encourage the improvement of the overall building energy efficiency. These improvements can be classified into passive and active ones. The energy conservation measures involve active actions, such as electric lighting, equipment, heating, ventilation and air conditioning (HVAC), etc., oriented towards the use of modern facilities with higher efficiency and low energy consumption, while passive actions are oriented towards the reduction of the energy demand over the life of the building. The passive actions can be incorporated within the construction elements, like envelope insulation and fenestration, or they can be integrated as external elements that can significantly reduce the cooling demand. However, it is not always possible to replace the glazing or the insulation layers, considering the complexities coming from, for example, the historical relevance of a building or the cost for the privates.

Scientific Innovation and Relevance

(max 200 words)

In these cases, a lightweight, non-impacting and inexpensive solution, such as the installation of an external second skin layer on the façade, can be seen as a foreseeable passive solution to improve the thermal performances of the building envelope [2].

In this paper, the energy and environmental impacts of passive retrofit actions on an existing building are evaluated in terms of primary energy saving, carbon dioxide equivalent emissions and simple pay-back period [3]. The study focused on office building and is aimed at both proposing a general operational methodology and highlighting a best practice for the Italian territorial context. The primary energy consumption, the carbon dioxide equivalent emissions and cost-effectiveness, associated to the current scenario of the case study, have been evaluated through the dynamic simulation software TRNSYS, across a whole year. The simulation results associated to a reference office building have been compared with those achievable by adopting a passive retrofit action on the building envelope. In particular, the refurbishment consists of the installation, without invasive interventions, as a second skin, of a light innovative flexible PVC-coated polyester fabric [4] on the façade of the reference building.

Preliminary Results and Conclusions

(max 200 words)

Different arrangements and control strategies have been considered for the second skin, specifically tailored on the characteristics of the polyester fabric. Both the energy and environmental comparison have been carried out according to the Italian scenario. The performed comparison among the current status and the possible future scenarios allowed to evaluate the potential benefits in terms of primary energy saving, carbon dioxide equivalent emissions reduction, and cost-effectiveness, assessing the advantages of each proposed retrofit action. In particular, the results highlighted that a seasonal control strategy, along with a proper integration of an insulation layer in the second skin system, allowed for a reduction of the cooling energy associated to the whole building up to 30%.

Main References

(max 200 words)

[1] M. Scorpio, G. Ciampi, A. Rosato, L. Maffei, M. Masullo, M. Almeida, S. Sibilio. Electric-driven windows for historical buildings retrofit: Energy and visual sensitivity analysis for different control logics, Journal of Building Engineering, Volume 31, September 2020, 101398. https://doi.org/10.1016/j.jobe.2020.101398

[2] F. Ascione, N. Bianco, G. Maria Mauro, D.F. Napolitano. Building envelope design: Multi-objective optimization to minimize energy consumption, global cost and thermal discomfort. Application to different Italian climatic zones. Energy 2019;174:359–74. https://doi.org/10.1016/j.energy.2019.02.182.

[3] G. Angrisani, E. Entchev, C. Roselli, M. Sasso, F. Tariello, W. Yaïci. Dynamic simulation of a solar heating and cooling system for an officebuilding located in Southern Italy. Applied Thermal Engineering, Volume 103, 25 June 2016, Pages 377-390. https://doi.org/10.1016/j.applthermaleng.2016.04.094

[4] Schueco. PVC-coated polyester Fabric. https://www.schueco.com/de-en/fabricators/products/facades/textile-facades/facid65 (accessed July 12, 2020).



13:12 - 13:18

Study of optimal control strategies for an energy production system using thermal mass of buildings

Charbel Salameh1,2, Bruno Peuportier2, Patrick Schalbart2

1Accenta; 2Centre Efficacité énergétique des Systèmes Mines Paristech

Aim and Approach

(max 200 words)

During the operation phase, HVAC systems (heating, cooling, and domestic hot water) represents up to 50% of buildings total energy consumption, and 75% of GHG (Greenhouse Gas) emissions in France. Photovoltaic and solar thermal production, geothermal heat pumps, BTES (Borehole Thermal Energy Storage), and short-term thermal storage (in hot or cold water tanks) can be associated to reduce cost and related emissions.

In this context, real-time energy management strategies adapted to this type of complex systems is investigated. Determining an energy management strategy for such systems, taking into account buildings thermal capacity, requires adequate building and system models that can evaluate energy loads with good precision in a reasonable calculation time for real-time application.

Dynamic thermal simulation is used in order to evaluate the consumption and production profiles of typical buildings and the associated energy system. An appropriate optimisation technique with an objective function is applied in order to determine optimal strategies.

Scientific Innovation and Relevance

(max 200 words)

Considering the large impact of the buildings energy consumption and GHG emissions, methods and solutions are developed in order to decrease the energy consumption and the environmental impact of the sector. This study presents an innovative solution that is based on thermal energy storage using BTES.

In this first approach, we consider using a geothermal borehole model with a Ground Source Heat Pump (GSHP) coupled to a building model including an occupancy model and meteorological data. The goal is to optimise the control in real-time of the energy production and storage system based upon the calculation of the heating/cooling needs of the building. This optimisation takes into consideration the cost of the energy production and the COP of the GSHP influenced directly by the energy exchanged with the BTES.

The novelty of this model lies in the simultaneous multi-system simulation and optimisation taking into consideration the energy storage in the building thermal mass and in the BTES. The study aims at minimising the cost and impact of the thermal energy production. In addition, the system efficiency and building thermal needs profile can be optimised by allowing a temperature set point variation within the limits of occupants’ comfort.

Preliminary Results and Conclusions

(max 200 words)

The optimisation procedure was applied to a multi-family residential building of 4300 m² in the south of France.

Taking into consideration an hourly electricity price and a maximal and minimal limit for the temperature set point in the building, the results show a load shifting of the energy demand by shifting the demand from peak hours to low-cost hours. This is made possible by storing the energy in the thermal mass of the building, increasing the temperature during off-peak hours to an acceptable limit within the respect of the occupants’ comfort.

The optimisation takes into account a short-term horizon considering the building dynamic, and a long-term horizon for the BTES which can range from a minimum of one year to a twenty year period to ensure the temperature balance in the ground storage, thus optimising the efficiency of the heat pump.

Early results show a decrease of energy consumption cost between 10% and 15%.

Main References

(max 200 words)

Favre B., Peuportier B., Application of dynamic programming to study load shifting in buildings, Energy and Buildings 82 (2014) 57–64

Frapin, M., Chaplais, F., Schalbart, P. and Peuportier, B., Optimal control of heating in a two-zone building using price decomposition-coordination method, 31st International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, June 2018, Guimarães - Portugal.

Malisani, P., Favre, B., Thiers, S., Peuportier, B., Chaplais, F. and Petit, N. Investigating the ability of various buildings in handling load shiftings, Power Engineering and Automation Conference, Wuhan, septembre 2011

PEUPORTIER, B. et SOMMEREUX, I. B., 1990. Simulation tool with its expert interface for the thermal design of multizone buildings. In : International Journal of Solar Energy. 1 janvier 1990. Vol. 8, n° 2, p. 109‑120. DOI 10.1080/01425919008909714.

Robillart, M., Schalbart, P., Chaplais, F., Peuportier, B., Model reduction and model predictive control of energy-efficient buildings for electrical heating load shifting, J. Process Control (2018), 11:3, 294-308, https://doi.org/10.1080/19401493.2017.1349835

Robillart, M., Schalbart, P., Peuportier, B., Derivation of simplified control rules from an optimal strategy for electric heating in a residential building. Journal of Building Performance Simulation, July 2017. doi: 10.1080/19401493.2017.1349835.



13:18 - 13:24

Effect of introducing hybrid power system for housing

Saori Nakao1, Yasuyuki Shiraishi1, Yusuke Shigematsu2

1The University of Kitakyushu, Japan; 2Saibugas Co., Ltd., Japan

Aim and Approach

(max 200 words)

In this research, we propose a three-cells cooperation system that combines a fuel cell system (FC) and a storage battery system (BT) in a photovoltaic power generation (PV) to utilize renewable energy as the main power source in a house.[1,2] FC can be operated according to the power generation status of renewable energy because it can supply power stably and generate power at any time. In addition, FC can also use the waste heat generated by power generation for hot water supply. BT can charge and discharge excess power of PV that has not been consumed by itself. In this report, as the previous step of the demonstration experiment to be conducted in the future, we conduct a case study of annual energy simulation for a house with a three-cells cooperation system. The purpose of this study is to clarify the optimum operation method of a three-cells cooperation system by comparing simulation cases from the viewpoint of the energy saving and the economic efficiency. The energy saving evaluation items are annual energy consumption, energy self-sufficiency rate of the house, and CO2 emissions, and the economic evaluation items are the operating cost and energy payback time (EPT) when introducing each device.

Scientific Innovation and Relevance

(max 200 words)

Although renewable energies such as PV and wind power generation are environmentally friendly and abundant resources that can be easily obtained at low cost, there is a problem that the amount of power generation changes depending on the weather. Therefore, a stable power supply becomes possible by combining renewable energy with a device that can stably supply electric power or a device that can store them.[3,4] Tsuneoka et al. [5] proposed an operation method using heat pump water heater(HPWH) and BT in combination with PV, and showed the economic superiority of autonomous operation by introducing BT. Akimoto et al. [6] investigated the operation method by introducing electric vehicle (EV) to consume excess power of PV, and proposed operation methods that improve energy self-sufficiency rate of the house according to the frequency of EV use. In this way, methods of combining various devices with renewable energy have been proposed, but there are not many case studies that compare multiple operation methods from the viewpoint of energy saving and economic efficiency assuming actual operation. In this report, we conduct a case study of the operation method for a house with a three-cells cooperation system assuming actual operation.

Preliminary Results and Conclusions

(max 200 words)

By introducing a three-cells cooperation system in the house, it has become possible to supply power without using external power as much as possible. For the reason, energy self-sufficiency rate of the house was increased, and annual energy consumption and CO2 emissions were decreased. Since the power purchased from the grid has been significantly reduced, the operating costs have been reduced as well. Based on the above results, the effectiveness of the three-cells cooperation system was shown from the viewpoint of both the energy saving and the operating costs.[1,2] Regarding EPT, although the initial cost of PV and FC has decreased, the initial cost of BT is still high, so it took a considerable number of years to recover them. However, it was suggested that EPT could be significantly shortened by using the Feed-in Tariff, that electricity company purchases electricity generated from renewable energy at a fixed price, and selling excess power of PV.

Main References

(max 200 words)

[1] Y.Shigematsu et al, Optimal control of a household fuel cell system in a three-cells cooperation system Part1 Project summary for building new energy utilization model, Heating, Air-Conditioning and Sanitary Engineers of Japan (in press, in Japanese).

[2] S.Nakao et al, Optimal control of a household fuel cell system in a three-cells cooperation system Part2 Examination of energy saving effect and economic efficiency by numerical simulation, Heating, Air-Conditioning and Sanitary Engineers of Japan (in press, in Japanese).

[3] Jijian Lian et al, A review on recent sizing methodologies of hybrid renewable energy systems, Energy Conversion and Management, Vol.199.(2019), pp.1-23.

[4] T.Wakui et al, Optimal operations management of residential energy supply networks with power and heat interchanges, Energy and Buildings, Vol.151.(2017), pp.167-186.

[5] Y.Tsuneoka et al, Operation Method for Self-Consumption of Surplus Power Considering Comfort in a Zero Energy House, Heating, Air-Conditioning and Sanitary Engineers of Japan, No.10.(2017), pp.293-296 (in Japanese).

[6] M.Akimoto et al, Operational strategies for self-consumption considering the use of an electric vehicle ㏌a net zero energy house, Journal of Environmental Engineering (Transactions of AIJ), Vol.770.(2020), pp.277-287 (in Japanese).



13:24 - 13:30

Activation of the building thermal mass to store PV surplus energy

Arno Dentel, Christina Betzold

Technische Hochschule Nürnberg, Germany

Aim and Approach

(max 200 words)

Since 2018, a terraced house complex with shared energy system is monitored and evaluated regarding PV self-consumption and efficiency. Beside heat pumps and photovoltaics (PV), different kind of storage units are integrated and used to store PV surplus. Thermal storage units for heating and domestic hot water as well as an electrical storage are integrated into the higher-level control system and are charged selectively. However, since the capacity limits have been reached, additional storage options are interesting. The thermal mass of the building offers additional potential to store PV surplus energy. This paper evaluates the operation of thermal mass activation for the terraced house complex in order to increase the PV self-consumption and decrease the grid consumption.

The simulation study of thermal mass activation is realized in TRNSYS. Increasing the room set point temperature of 20 °C by 2 K during PV production, aims to a reduction of the grid consumption by 47 % and an increase of PV self-sufficiency from 23 % up to 64 %. At the same time, the mean deviation of the room set temperature increased from 1.7 K to 2.0 K. The results are compared to real measured data from the terraced house

Scientific Innovation and Relevance

(max 200 words)

In this work, a control strategy is investigated in simulation and real operation, which activates the thermal building mass by increasing the setpoint in the entire building. Figure 1 shows the process of the control strategy, which depends on the available PV power. As soon as a PV power of 1 kW is exceeded, the setpoint is increased by 1 K to 6 K, depending on the variant. If the PV power is less than 1 kW, the default setpoint, e.g. 20 °C, is set. In real operation the interface between control strategy and building energy management system is realized by a SQL Server Database.

Preliminary Results and Conclusions

(max 200 words)

The simulation results show that the activation of the thermal building mass with PV power offers good potential for reducing grid consumption while maintaining thermal comfort. Likewise, the operating costs can be reduced both with and without the EEG levy but with the EEG levy, the cost savings drop again after 3 K. A setpoint increase of 2 K provides the best result. The energy and financial results do not improve thereafter. The thermal comfort only deteriorates strongly with very high setpoint increases of 6 K.

The assessment of the storage potential shows that a room temperature increase from 20 C to 22 °C leads to a thermal power of 6 kW to 8 kW over a period of 6 hours. After approx. 6 hours, the thermal power is reduced because some rooms have already reached their setpoint. Due to the room-by-room building model, there is no complete switching off of the thermal power, as some rooms are already heated again depending on their temperature.In addition, the activation of the thermal building mass was implemented in the control of the terraced house complex in November 2020.

Main References

(max 200 words)

EEG, 2020: German Renewable Energies Law

University of Madison-Wisconsin, 2017. TRNSYS-TRaNsient SYstems Simulation, Solar Energy Laboratory,. Version 18.1.



13:30 - 13:36

Impact of implementing air-conditioning systems on the school building stock in Brazil considering climate change effects: a bottom-up benchmarking

Matheus Soares Geraldi, Mateus Vinicius Bavaresco, Veronica Gnecco, Enedir Ghisi, Michele Fossati

Federal University of Santa Catarina, Brazil

Aim and Approach

(max 200 words)

The study of the building stock is a key knowledge to improve energy performance and enhance indoor environmental quality. In Brazil, energy policies are still in their first steps [1]. This study is based on a previous work that assembled and analysed evidence-based data of public schools in Brazil [2], which revealed that around 90.1% of them are not equipped with adequate air-conditioning. Those systems are responsible for enhancing indoor thermal conditions, but also increase the energy use intensity [3]. Meanwhile, air-conditioning is being gradually implemented in schools according to the uninformed culture that only those systems provide adequate thermal conditions.

This paper aims to estimate how much the average energy use intensity (EUI) of the building stock will increase due to implementing air-conditioning in schools. For this purpose, EnergyPlus simulation was employed using reference buildings. Parametric simulations were adopted to represent the actual stock conditions for a sample of 378 buildings, and a calibration process fitted the simulated and actual whole-building energy consumption. Then, the calibrated models were used to simulate scenarios of air-conditioning implementations. Finally, predicting the increasing of EUI allows the evaluation of energy efficiency strategies instead of just implementing air-conditioning in the near future.

Scientific Innovation and Relevance

(max 200 words)

The scientific innovation of this study relies on the method employed, which takes advantage of building stock modelling techniques to estimate future trends of the performance of the building stock. Benchmarking is a useful practice to evaluate if a building is efficient or not by comparing it against its pairs. Developing a benchmarking practice requires methods that take into consideration stock data. It usually adopts reference buildings and considers simulation models to establish the benchmark by regressive models – the reference energy performance of a building typology according to determined conditions. Advances in benchmarking methods are available in the literature; however, they are usually related to high-granularity data, specific focuses or their countries or regions [4]. In Brazil, a static benchmarking method was developed for bank branches [5] and high-rise buildings [6]. However, a comprehensive benchmarking method that considers future trends for school building stock is pioneering.

The relevance is expressed by the importance of measuring the carbonisation effect of the implementation of air-conditioning systems in the public-school stock in Brazil. Furthermore, by estimating this impact at stock-level, it is possible to propose passive and smart strategies instead of the unconscious implementation of air-conditioning systems.

Preliminary Results and Conclusions

(max 200 words)

So far, the building stock was characterised. It was observed that only 12.95% out of all classrooms of the stock have air-conditioning. Similarly, only 32.7% of the administrative rooms and 31.9% of the labs have air-conditioning. Two specific schools that had air-conditioning installed in 2016 and 2017 were analysed. The first school had and EUI of 11.9 kWh/m² before the implementation and 34.6 kWh/m² after. The second case presented 8.1 kWh/m² before and 15.8 kWh/m² after. Both cases presented an expressive increasing in EUI, as expected.

The use of a standard design in a national perspective does not support the use of passive strategies for energy efficiency, which are inherently dependent on the building context [7]. Then, the educational department opts to implement air-conditioning to boost thermal condition as a general rule. However, the utilisation of passive strategies such as increasing ceiling insulation, smart utilisation of the natural ventilation and improving shading devices could improve the thermal condition and reduce cooling loads. Finally, there is the possibility to take advantage of this standard design and propose standard solutions according to the building context.

Main References

(max 200 words)

[1] A.P. Melo, M.J. Sorgato, R. Lamberts, Building energy performance assessment: Comparison between ASHRAE standard 90.1 and Brazilian regulation, Energy Build. 70 (2014) 372–383. doi:10.1016/j.enbuild.2013.11.080.

[2] M.S. Geraldi, E. Ghisi, Mapping the energy usage in Brazilian public schools, Energy Build. 224 (2020) 110209. doi:10.1016/j.enbuild.2020.110209.

[3] T.S. Saraiva, E.M. da Silva, M. Almeida, L. Bragança, Comparative study of comfort indicators for school constructions in sustainability methodologies: Schools in the amazon and the southeast region of Brazil, Sustain. 11 (2019). doi:10.3390/su11195216.

[4] M.S. Geraldi, E. Ghisi, Building-level and stock-level in contrast : A literature review of the energy performance of buildings during the operational stage, Energy Build. 211 (2020) 109810. doi:10.1016/j.enbuild.2020.109810.

[5] E.H. Borgstein, R. Lamberts, Developing energy consumption benchmarks for buildings: Bank branches in Brazil, Energy Build. 82 (2014) 82–91. doi:10.1016/j.enbuild.2014.07.028.

[6] T. Alves, L. Machado, R.G. de Souza, P. de Wilde, Assessing the energy saving potential of an existing high-rise office building stock, Energy Build. 173 (2018) 547–561. doi:10.1016/j.enbuild.2018.05.044.

[7] P. de Wilde, Building Performance Analysis, John Wiley & Sons Ltd, 2018.



13:36 - 13:42

Borehole latent energy storage system integrated with solar thermal collectors and heat pumps

Parham Eslami Nejad, Arash Bastani, Alain Nguyen, Etienne Saloux

CanmetENERGY, NRCan, Canada

Aim and Approach

(max 200 words)

In this study, low temperature borehole thermal energy storage integrated with thermal solar collectors and heat pumps is investigated for the Drake Landing Solar Community. Each borehole in the field is equipped with two independent U-pipe circuits and saturated sand backfill. Heat pumps and solar collectors are connected to these U-pipe circuits independently. Simultaneous heat injection and extraction to/from the boreholes can be achieved through this configuration without the need for an above-ground short-term storage system.

Scientific Innovation and Relevance

(max 200 words)

Contrary to the existing system (Sibbitt et al. 2012), the 52-home community is conditioned using reversible heat pumps. In the heating mode, which is the dominant in the extreme cold conditions of Okotoks (Alberta, Canada), heat pumps extract heat from the boreholes and freeze saturated sand backfill. Solar thermal energy is injected to balance out the ground thermal load and to melt frozen backfill for storing latent thermal energy. Implementing some PV modules is also investigated to partially compensate power used by the heat pumps.

Preliminary Results and Conclusions

(max 200 words)

A detailed numerical model of the system has been developed to evaluate the new concept. This study summarizes different effects of the borehole latent energy storage (BLES) system on the overall system performance and characteristics. Although solar fraction is reduced and the heat pump net electricity consumption from the grid is positive, simulation results confirmed significant reduction of solar storage temperature, total required borehole depth, solar collector areas, and borehole field footprint. This concept can be used to develop a new generation of low temperature solar community with integration of BLES system and heat pumps.

Main References

(max 200 words)

Sibbitt, B., McClenahan, D., Djebbar, R., Thornton, J., Wong, B., Carriere, J., Kokko, J., 2012. The Performance of a High Solar Fraction Seasonal Storage District Heating System – Five Years of Operation. Energy Procedia. 30, 856–65.



13:42 - 13:48

Simulation-based analysis of the load-shifting potential of Heat Pumps in Multi-Family Houses using co-simulation

Daniel Schmidt, Sabine Hoffmann

TU Kaiserslautern, Germany

Aim and Approach

(max 200 words)

Due to the growing expansion of renewable energies (RE), electricity grids will face increasing challenges in the future. A rising share of renewables is required because of the finite nature of fossil fuels and in order to achieve the climate targets set. The feed-in of electricity from RE is highly fluctuating and hard to control. Demand-Side-Management is a way to adjust the demand of electricity to its generation.

In our research project we focus on heat pumps (HP) as a Power-to-Heat solution. Based on the good efficiency, HPs are increasingly used to heat buildings. This approach is particularly interesting because heat can be stored more easily compared to electricity as most residential buildings have a thermal storage. By using thermal storage systems, generation of heat can be decoupled from demand in terms of time. This contribution examines how heat generation in multi-family houses (MFH) can be shifted to grid-friendly times using model predictive control (MPC) and HPs.

Scientific Innovation and Relevance

(max 200 words)

In a first step, various simulation models were created to investigate the flexibility of heat generation in different buildings. The research focuses on typical MFHs from Germany, France, Belgium and Luxembourg. For each country a reference building was modelled and represented in TRNSYS. The building models were modified to represent different years of construction with according heating demands. In addition, different storage volumes were modelled in TRNSYS to vary the existing heat capacity. The MPC system was programmed in MATLAB. Taking weather data and grid signals into account, it designs an operating plan of a heat pump for a horizon of 48 hours. The simulation results show that the developed MPC in combination with HPs can represent one possible solution to the challenges of energy transition.

Furthermore, we will explain the chosen solution for co-simulation of models in MATLAB and TRNSYS using the BCVTB (Building Controls Virtual Test Bed) platform. Based on the experiences gained, it can be shown how the advantages of individual simulation programs can be used and how the range and relevance of investigations can be increased by combining different software.

Preliminary Results and Conclusions

(max 200 words)

The results of the project specify the extent to which the electricity requirement for heat generation can be controlled in MFHs of different years of construction. A special focus is set on the flexibility of the different buildings. The simulation results show how the operating time of the heat pump in combination with the controller can be shifted to support the electricity grid.

Additionally, the results point out that it may also have a financial advantage for end consumers to use a control system to exploit the cheapest possible electricity signals. Variable tariffs could provide incentives for electricity consumption in the future. The contribution also evaluates the potential for financial savings.

Altogether, the outcome of the project shall prove that Power-to-Heat in buildings plays an important role in the energy transition. The solution presented cannot solve the major problem of fluctuating generation from renewables and the necessary expansion of the electricity grids, but it can certainly make a contribution to stabilizing the grids in the future.

Main References

(max 200 words)

This contribution was carried out during the Interreg research project PtH4GR²ID (Power-to-Heat for the Greater Region's Renewables Integration and Development), in which researchers from Germany, France, Belgium and Luxembourg are collaborating. All the models used in this study were developed within the project and details and further information can be seen in the corresponding reports (see homepage: http://www.pth4gr2id.com/).

More detailed information on the control system used can also be found in the following publication:

Röhrenbeck, S.; Benzarti, A.; Wellßow, W. H.; Maar, K.; Hauffe, P.; Maul, J.; Pahn, M.; Tersluisen, A.; Gündra, H.: Prädiktive Betriebsoptimierung drehzahlvariabler Wärmepumpen in Kombination mit preisvariablen Stromtarifen. VDE Kongress, Mannheim, 2016

The programs used to perform the simulations are TRNSYS (Transsolar, http://www.trnsys.com/) and MATLAB (MathWorks, https://de.mathworks.com/). The BCVTB platform (Lawrence Berkeley National Laboratory, https://simulationresearch.lbl.gov/bcvtb/FrontPage) was used to connect the two software.



13:48 - 13:54

Operational control of earth-to-air heat exchanger using reinforcement learning

Kento Tomoda1, Yasuyuki Shiraishi1, Dirk Saelens2,3

1The University of Kitakyushu, Fukuoka, Japan; 2KU Leuven, Department of Civil Engineering, Building Physics & Sustainable Design Section, Leuven, Belgium; 3EnergyVille, Genk, Belgium

Aim and Approach

(max 200 words)

This research focuses on the development of an optimal control system for earth to air heat exchangers (EAHE). During the operational phase, EAHE control system should determine optimal settings for airflow rate ensuring that the indoor air quality and the heat exchange are maximized. The EAHE control system should determine optimal settings for airflow rate ensuring that the indoor air quality and the heat exchange are maximized. It is, however difficult to optimize the system by conventional control methods since the response of the control is noticeable only a few days later. Our main purpose was to explore the applicability of an optimal control for EAHE by reinforcement learning (RL) controls which do not require the construction of control rules. We conducted the analysis with a CFD based simulator [1] as the RL environment and Proximal Policy Optimization [2] as the RL algorithm. The state which was obtained from the CFD was defined such as outside air temperature and surface temperature in the system. Actions were the binary value whether introduce outside air through the EAHE or not. Rewards were the obtained pre-cooling quantity through EAHE and the occurrence of condensation at representative point in the system.

Scientific Innovation and Relevance

(max 200 words)

In this study, we conducted RL controls for the summer season using CFD-based high-precision long-term performance prediction simulator developed by us [1] as an RL environment. Wei et al [3] built learning environments of RL with an HVAC system which was EnergyPlus model and investigated the controllability for HVAC systems by Q learning and Deep Q-Network (DQN). The research in [4] implemented HVAC control by DQN algorithm with the indoor thermal comfort and energy consumption as rewards. RL could be applied to complex problems with a large number of state variables, such as Building Automation System (BAS), and is attracting attention as a next-generation control method. Training phase on RL, it requires a huge number of simulation trials. However, EAHE simulation requires long term analysis since its huge heat capacity and complex geometry. For this reason, it is difficult to simulate for EAHE many times. Considering the implementation for BAS, a highly accurate simulator is required because it takes time for relearning if there is a deviation between the prediction results and the real world. However, there was no research about application of RL control to EAHE due to difficulty in establishing an appropriate RL environment of EAHE.

Preliminary Results and Conclusions

(max 200 words)

As the learning progressed, the obtained pre-cooling quantity was increased and the condensation time ratio in the system which correlation with airborne fungi of fresh air after passing through the system tended to decrease. In the current implementation, it was suggested that the control by RL could maximize the obtained pre-cooling quantity while suppressing condensation. Since only RL control was mentioned in this paper, comparison conventional control methods with that is a subject for future study.

Main References

(max 200 words)

[1] Kento Tomoda et al. “Annual Prediction Method for the Pre-Cooling/Heating Performance of Earth-to-Air Heat Exchanger using Underground Air Tunnel”. Proceedings of the 11th International Conference on Industrial Ventilation. Vol.1. (2015). pp. 339-346.

[2] John Schulman et al. Proximal Policy Optimization Algorithms. arXiv preprint. arXiv: 1707.06347. (2015).

[3] Tianshu Wei et al. “Deep Reinforcement Learning for Building HVAC Control”. Design Automation Conference. (2017). pp. 1-6.

[4] William Valladares et al. “Energy optimization associated with thermal comfort and indoor air control via a deep reinforcement learning algorithm”. Building and Environment. Vol.155. (2019), pp. 105-117.



13:54 - 14:00

Distribution of potential savings from urban-scale energy modeling of a utility

Brett Bass1, Joshua New2

1The University of Tennessee; 2Oak Ridge National Laboratory

Aim and Approach

(max 200 words)

While urban-scale building energy modeling is growing increasingly mature in data sources, algorithms, and empirical validation, there is still a need for best practices, guidelines, and standards for industry-accepted decision metrics relevant to specific use cases. Case studies are needed to inform such efforts. In addition, successful applications are need to motivate investment by, and in partnership with, utilities to scale grid-interactive efficient building technologies, realize aspirations of smart homes and cities, and dynamically dispatch load (rather than generation) in a way that stabilizes and reduces the cost of critical energy infrastructure. In partnership with the Electric Power Board of Chattanooga, TN, OpenStudio and EnergyPlus models were created of over 179,000 buildings and empirically validated against 15-minute whole-building electrical consumption of each building. Eight energy/demand-related measures relevant to nine utility-defined use cases are evaluated to showcase statistical distributions over the entire building stock of potential savings for energy, demand, emissions, and cost.

Scientific Innovation and Relevance

(max 200 words)

Most urban-scale building energy modeling projects lack scalability due to use of geographically-limited data sources (e.g. tax assessor’s data). Lessons learned from categorizing and analyzing 37 data sources [1] have been contrasted with tax assessor data to define 19 fields that may be useful in developing a comparison matrix with examples comparing/contrasting traditional vs. non-traditional urban-scale data sources [2]. New data sources and algorithms were applied iteratively to create slightly-different digital twins of all buildings in the 1400 km2 service area of a utility. By comparing the simulated energy use of each digital twin to actual 15-minute energy data from each building, we were able to prioritize the value of data source and algorithm combinations that tended to result in energy models that more closely match the true electrical consumption. These baselines were then modified to quantify energy, demand, emissions, and cost savings prior to potential program rollout, targeted marketing, and business model decisions for utility-prioritized use cases [3]. This study will review contributions to the data, algorithms, taxonomy, and value of data layers for specific use cases relevant to a utility.

Preliminary Results and Conclusions

(max 200 words)

While empirical validation is increasingly common, high-resolution measured energy data is still relatively difficult to attain and is typically done for dozens to ~200 buildings in previous literature. This study performs empirical validation of 179,000 buildings, providing a larger sample size with greater statistical confidence in the final results.

Instead of reporting average savings for energy (kWh), this study will focus primarily on the contributions involving the distribution (e.g. box-and-whisker plots) of savings not only for energy but also for electrical peak demand (kW), emissions (kg), and cost ($ US dollars).

Multiple building technologies are evaluated including roof insulation, envelope sealing, more efficient lighting, smart thermostats, more efficient HVAC or water heater, and different HVAC or water heater types. As an example, smart-thermostat for utility-signaled pre-conditioning of buildings by 4.4°C two hours prior to peak demand saves on average 27% of a building’s electrical demand but varies significantly from 0 to 93% across the 179,000 buildings. Aggregation of building-specific savings to utility-scale savings offers reduced risk for the financing and implementation of utility-scale savings. Upon approval by the utility, savings will be presented as average/building or percent to allow rough estimation of potential savings by other utilities.

Main References

(max 200 words)

[1] Yuan, Jiangye, New, Joshua R., Sanyal, Jibonananda, and Omitaomu, Olufemi (2015). "Urban Search Data Sources." ORNL internal report ORNL/TM-2015/397, July 31, 2015, 70 pages.

[2] New, Joshua R., Adams, Mark, Garrison, Eric, Bass, Brett, and Guo, Tianjing (2020). "Scaling Beyond Tax Assessor Data.” ASHRAE/IBPSA-USA 2020 Building Performance Analysis Conference & SimBuild (BPACS), Chicago, IL, Aug. 12-14, 2020.

[3] New, Joshua R., Adams, Mark, Im, Piljae, Yang, Hsiuhan, Hambrick, Joshua, Copeland, William, Bruce, Lilian, Ingraham, James A. (2018). "Automatic Building Energy Model Creation (AutoBEM) for Urban-Scale Energy Modeling and Assessment of Value Propositions for Electric Utilities." In Proceedings of the International Conference on Energy Engineering and Smart Grids (ESG), Fitzwilliam College, University of Cambridge, Cambridge city, United Kingdom, June 25-26, 2018.



14:00 - 14:06

Dynamic simulation of a radiant ceiling panel incorporating PCMs for building cooling and heating applications

Andres Gallardo, Umberto Berardi

Ryerson University, Canada

Aim and Approach

(max 200 words)

Experimental and numerical studies have demonstrated the benefits of thermally activated building systems (TABS) in terms of thermal comfort and energy efficiency. However, one downside of TABS is that the system has to be incorporated in the building from the design stage, which limits its application to new buildings. To encourage the application of high thermal mass radiant systems in refurbishment, the authors developed a radiant ceiling panel system with incorporated PCM (PCM-RCP). The focus of this study is on the control strategy to operate the system, to meet both heating and cooling demands of a typical office building. Whole-building energy simulations have been used for evaluating the performance of the PCM-RCP system operating under the proposed control strategy.

Scientific Innovation and Relevance

(max 200 words)

The authors aim to provide criteria to effectively design, size, and control radiant ceiling panels with integrated PCM for building heating and cooling applications. This paper explicitly presents the control of the proposed system, that has been developed as part of an integrated process that also includes the design and dimensioning of the system. The proposed control strategy take into consideration previous findings that indicated that radiant cooling systems with PCM have an optimum performance when the cycle of melting and solidification is completed as much as possible. Based on the radiant cooling ceiling panel surface temperature that represents the melting temperature of the incorporated PCM, a control algorithm is proposed for year-round automated operation, which meets the comfort requirements, is simple to implement and leads to an energy-efficient operation.

Preliminary Results and Conclusions

(max 200 words)

Results indicate that the control strategy can be regarded as effective as it can respond well to changes in cooling and heating demand, meet the thermal comfort requirements, is simple to implement, and can lead to an energy-efficient operation due to the capability to operate only at night-time. Results also show that for cooling dominated climates, a melting temperature of 21℃ is desirable to increase the passive cooling power of the system. However, in climates where both cooling and heating are required, a melting temperature of 24℃ results in better thermal performance.

Main References

(max 200 words)

- Jobli, M. I., Yao, R., Luo, Z., Shahrestani, M., Li, N., & Liu, H. (2019). Numerical and experimental studies of a Capillary-Tube embedded PCM component for improving indoor thermal environment. Applied Thermal Engineering, 148, 466–477.

- Lehmann, B., Dorer, V., & Koschenz, M. (2007). Application range of thermally activated building systems tabs. Energy and Buildings, 39(5), 593–598.

- Raftery, P., Duarte, C., Schiavon, S., & Bauman, F. (2017). A new control strategy for high thermal mass radiant systems. In Proceedings of the 15th IBPSA Conference (pp. 755–764).

- Romaní, J., De Gracia, A., & Cabeza, L. F. (2016). Simulation and control of thermally activated building systems (TABS). Energy and Buildings, 127, 22–42.

- Tödtli, J., Gwerder, M., Lehmann, B., Renggli, F., & Dorer, V. (2007). Integrated design of thermally activated building systems and their control. 9th REHVA World Congress for Building Technologies - CLIMA.



14:06 - 14:12

The energy master planning process for districts

Matthias Haase

ZHAW, Switzerland

Aim and Approach

(max 200 words)

The energy master planning process for districts requires an analysis of different scenarios, which include new construction to different levels of energy efficiency, major renovation of all or some buildings comprising building stock under consideration with Deep Energy Retrofit of these buildings, minor renovations with energy-related scope of work, or demolition of some old buildings. Such analysis requires building energy modeling. In this research work we collected models of representative buildings from several countries and compared them.

Scientific Innovation and Relevance

(max 200 words)

Complex districts consist of buildings and outdoor spaces with specific needs. The use that different buildings and areas are put to affects energy consumption, whereas the different functional patterns and stakeholder groups influence energy use. They are also associated with specific requirements that make it relevant to consider different types of performance indicators.

In the scope of this analysis both ventilation indicators and requirements with a direct or an indirect effect on energy consumption in districts are identified. When defining the relevance of performance indicators; legal requirements (i.e. for work environment), ownership or authority over parts of the district (single buildings or a complex of buildings), and cultural context also come into play.

Preliminary Results and Conclusions

(max 200 words)

Energy can be considered to follow function because energy in the end is used to meet requirements defined by the activities that take place in a district. In each district, requirements are diversified by the type of activities/functions (residences, commercial (shops, retail), service (schools, restaurants, cafes, etc.), by the sizes of tenants rental spaces, or by the type of spaces (public areas, offices, parking etc.). The different activities can be characterized by functional patterns for various groups; – opening hours for commercial buildings will differ from operational hours for technical services and lighting. Facility operation has to meet the requirements of staff in commercial and cultural or service buildings before they open to the public. In districts, many tasks are performed outside of opening hours which require maintaining health and safety for the workers. Examples are maintenance and cleaning, sanitation and supply infrastructures, mobility and transport. In relation to this, the ratio of full operation of HVAC and lighting vs. opening hours or service hours is one index that could be used as a performance indicator.

Main References

(max 200 words)

Baer D, Haase M (2020) Energymaster planning on neighbourhood level: learnings on stakeholders and constraints fromtheNorwegian case ofYdalir, proceedings world sustainable built environment conference, Gothenburg, Sweden

BREEAM (2019) bre environmental assessment method. https://www.breeam.com/.

CASBEE (2019) Comprehensive assessment system for built environment efficiency. https://www.ibec.or.jp/CASBEE/english/.

EED—Directive 2012/27/EU of the European parliament and of the council of 25 October 2012 on energy efficiency. Energy Efficiency Directive. https://ec.europa.eu/energy/en/topics/energyefficiency/targets-directive-and-rules/energy-efficiency-directive.

EnergyPlan. Energy systems simulation tool. https://www.energyplan.eu/.

EPBD (2018) Directive (EU) 2018/844 of the European parliament and of the council of 30 May 2018 amending directive 2010/31/EU on the energy performance of buildings.

Fox K (2016) Energy master planning perspectives and best practices, presentation to the federal utility partnership working group, May 2016. Cincinnati, OH

Haase M, Lohse R (2020) Process of energy master planning of resilient communities for comfort and energy solutions in districts. In: IOP conference series: earth and environmental science, vol 352, number 1, IOP Publishing Ltd.

Huang Z, Yu H, Peng Z, Zhao M (2015) Methods and tools for community energy planning: a review. Renew Sustain Energy Rev 42(C):1335–1348 (Elsevier)

Jank R (2017) Annex 51: case studies and guidelines for energy efficient communities. Energy Build 154:529–537

LEED. Leadership in energy and environmental design. https://leed.usgbc.org/leed.html.



14:12 - 14:18

Case study of an NZEB (renovation) with 7 years measurement data – what can a designer learn from it?

Matthias Haase

ZHAW, Switzerland

Aim and Approach

(max 200 words)

A typical residential building from 1937 located near Wuerzburg in Germany, was deep retrofitted in 2013. Roof, façade and ceiling in the basement were highly insulated and thermal bridges were minimized. Windows were replaced with three-layered glazed windows with wood-aluminium windows. A compact unit (balanced ventilation system with integrated air-to-water heat pump) was installed together with an 8 KW PV system with a south-west orientation and 50 degrees angle (roof-integrated). The ventilation ducts were integrated into the existing chimneys. Residential appliances/white goods (Refrigeration, Laundry, Dishwashing) were installed/replaced by A+++ equipment. Cooking equipment was replaced by induction device. Lighting fittings were replaced with LED in the whole building.

The simulations of energy balance and load profiles (in IDA ICE) match well with measurements. Self-consumption and export of electricity to the grid was monitored. The results show variations in self-consumption.

Scientific Innovation and Relevance

(max 200 words)

The paper presents Monitoring data from 7 years performance of a NZEB. This represents a very comprehensive retrofitting towards plus energy level. Energy consumption and production as well as usage patterns and load profiles were monitored over a period of one year.

Besides key performance indicators for energy production and energy use it is interesting to monitor different KPI for self-consumption. Energy costs is another useful KPI.

The results have implications for energy load profiles which represent a new type of grid load that needs further recognition in planning of renovation work.

Preliminary Results and Conclusions

(max 200 words)

This paper reports a case study of deep retrofitting of a residential building towards plus energy level. Energy consumption and production as well as usage patterns and load profiles were monitored over a period of one year. The simulations of energy balance and load profiles match well with measurements. Self-consumption and export of electricity to the grid was monitored. The results show variations in self-consumption. Annual self-consumption varied between 17% (2015) and 22% (2020).

Main References

(max 200 words)

Energy strategy for Europe (2012) Energy market country report 2011 – Belgium. European Commission.

BPIE 2013, Data Hub for the energy performance of buildings. Source: http://www.buildingsdata.eu/

EPBD. 2010. Energy Performance in Buildings Directive 2008/0223, European Commission, Brussels.

Kreditanstalt für Wiederaufbau (KfW), Energy efficient refurbishment (in German: Energieeffizientes Sanieren),updated in 2015, financial support program

Energieeinsparverordnung 2014, (EneV), http://enev-2014.info/, access date Jan 2016

Salom, J., Marszal, A.J., Widén, J., Candanedo, J. and Byskov Lindberg, K., (2014) Analysis of Load Match and Grid Interaction Indicators in NZEB with High-Resolution Data. IEA Task 40/Annex 52 Towards Net Zero Energy Solar Buildings.

 
13:00 - 14:30Session W2.9 (Online Track): Improving indoor environmental quality
Location: Virtual Meeting Room 3
Session Chair: Roberto Lamberts, UFSC
Virtual Meeting Room 3 
 
13:00 - 13:06

Smart ventilation control to minimize the infection risk with COVID-19 in office buildings

Zhihong Pang1, Pingfan Hu2,3, Xing Lu1, Qingsheng Wang2,3, Zheng O'Neill1

1J. Mike Walker '66 Department of Mechanical Engineering, Texas A&M University, College Station, TX, USA; 2Mary Kay O'Connor Process Safety Center, Texas A&M University, College Station, TX, USA; 3Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, USA

Aim and Approach

(max 200 words)

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as COVID-19, has already taken on pandemic proportions on a global scale. Many businesses have been delayed or even shut down in support of disease control amid the pandemic, leading to a rising number of social and economic issues in many countries.

In the context of strong advocates for reopening and economic recovery, this study aims to propose a novel ventilation control strategy to facilitate a smooth shift for the common office buildings from the normal mode, as which they were designed and operated by default, to the pandemic mode. To achieve this goal, firstly, a parametric computational fluid dynamics (CFD) analysis will be conducted to simulate the multiple operation scenarios of a VAV system under different occupancy and thermal load conditions. Secondly, based on the results of the parametric analysis, a scientific correlation between the CO2 concentration with the infection risk will be established to monitor the infection risk. Thirdly, a smart and novel ventilation control strategy will be developed by virtue of the quantitative relationship. This control strategy will then be evaluated by EnergyPlus simulations in terms of energy performance and effectiveness of risk mitigation.

Scientific Innovation and Relevance

(max 200 words)

Existing literature shows that ventilation control (sufficient fresh air) can help dilute the virus concentration in buildings and reduce the infection risk due to airborne transmissions. However, how to increase the ventilation rate through smart control strategies for public buildings during emergencies (e.g., pandemic) still remains unexplored.

As far as the authors are concerned, although there have been a few studies trying to investigate the minimum ventilation rate for disease control purpose, there is no similar research, which aims at directly associating the infection risk with the CO2 concentration using a comprehensive parametric CFD analysis. Besides, the proposed study is the first of its kind which takes both the energy performance and infection risk mitigation into the evaluation of a smart ventilation control. Since the AHU operation for most VAV systems in commercial buildings is relied on the CO2 sensing, the results of this study is more feasible to be implemented in the real buildings to bring actual benefits.

Preliminary Results and Conclusions

(max 200 words)

We have started to develop the CFD cases to prepare for the parametric analysis. The model setting and control scenario definition are still under discussion and yet to be finalized.

We have deployed a comprehensive environmental sensor network which measures the CO2 concentration, temperature, relative humidity, and light intensity for multiple pointes in a space for two complex rooms in a campus building. The key operation data of the HVAC system, e.g., the discharge airflow and temperature of the VAV box, the outdoor airflow rate, etc., has also been extracted from the Building Automation System (BAS) to facilitate the CFD model calibration.

Main References

(max 200 words)

Li, Yiping, et al. "Role of ventilation in airborne transmission of infectious agents in the built environment-a multidisciplinary systematic review." Indoor air 17.1 (2007): 2-18.

Yu, Ignatius TS, et al. "Evidence of airborne transmission of the severe acute respiratory syndrome virus." New England Journal of Medicine 350.17 (2004): 1731-1739.

Sundell, Jan, et al. "Ventilation rates and health: multidisciplinary review of the scientific literature." Indoor air 21.3 (2011): 191-204.

Chen, Qingyan. "Ventilation performance prediction for buildings: A method overview and recent applications." Building and environment 44.4 (2009): 848-858.

Zhang, Z., and Q. Chen. "Experimental measurements and numerical simulations of particle transport and distribution in ventilated rooms." Atmospheric environment 40.18 (2006): 3396-3408.

Greenough, Anne. "Role of ventilation in RSV disease: CPAP, ventilation, HFO, ECMO." Paediatric respiratory reviews 10 (2009): 26-28.

O'Neill, Zheng D., et al. "Energy savings and ventilation performance from CO2-based demand controlled ventilation: Simulation results from ASHRAE RP-1747 (ASHRAE RP-1747)." Science and Technology for the Built Environment 26.2 (2020): 257-281.



13:06 - 13:12

Numerical investigation of a novel diffuse wall ventilation: thermal comfort and cross-infection control effectiveness

Chen Zhang, Gaute Larsen Tveit, Truls Ramstad, Peter V. Nielsen, Rasmus Lund Jensen

Department of the Built Environment, Aalborg University, Denmark

Aim and Approach

(max 200 words)

A novel ventilation concept named as diffuse wall ventilation is proposed in this study and investigated by numerical simulations. The ventilation concept is similar to the diffuse ceiling ventilation[1][2], instead of using the suspected ceiling as an air inlet, the entire wall or large part of the wall serves as air inlet. The diffuse wall is made of textile material covered with vertically mounted lamellas, and the space behind the textile is utilized as a plenum to distribute air. Due to the large inlet area, the ventilated air is supplied into the occupied zone with very low velocity, and the airflow pattern in the room is dominated by the thermal buoyancy generated by the heat sources. A CFD model is developed to simulate the performance of diffuse ceiling ventilation in an Annex 20 room with two seated occupants [3][4]. The validated model is used to evaluate the thermal comfort, such as draft rate and temperature gradient, and cross-infection risk between two occupants under different flow rate and temperature difference scenarios. Finally, a parametrical study is performed to evaluate the impact of diffuse wall configurations. Three inlet configurations are investigated: full-wall inlet, half-wall inlet, and lamella inlet.

Scientific Innovation and Relevance

(max 200 words)

The diffuse wall ventilation concept is proposed initially as a part of an office renovation project, where the low ceiling and visible inlets and ducts are not accepted due to the space limitation and design preference, making the traditional ventilation concepts unsuitable. Even though the concept of supplying air from wall inlets have been widely researched and applied, such as displacement ventilation and stratum ventilation, supplying air from the entire wall has not been well documented and lack of knowledge on the ventilation performance. In the wake of the COVID-19 pandemic, increased awareness of a ventilation system’s ability to remove contaminants and inhibit the spreading of diseases is expected. Cross infection risk between two occupants in the office with diffuse wall ventilation is therefore evaluated, in addition to thermal comfort and system capacity.

Preliminary Results and Conclusions

(max 200 words)

The room with full-wall inlet is used as a baseline study, operated at three scenarios with supply temperature of 20, 17, 13 oC, and ACH of 8.3, 4.2, 2.5 h-1, respectively. The supply air falls towards the floor when it leaves the inlet and develops into a plane discharge flow when it reached the floor. The depth of the discharge flow depends on the supply air temperature. The discharge flow travels alone the floor and rises until meeting the heat sources, where it is comparable with displacement ventilation. The air velocity in the occupied zone is very low with diffuse wall ventilation, and max velocity is lower than 0.05 m/s in all cases. The temperature difference between the ankle and head height is less than 2 oC in all cases. Local air quality index at the inhaled air εexp is used to assess the cross-infection risk between two occupants. The simulation results indicate the case 1 (Ts= 20 oC and ACH= 8 h-1), provide the highest εexp of 2.2. The study of different diffuse wall inlet configurations shows that the room with half-wall inlet performs the best among three configurations in terms of thermal comfort and air quality.

Main References

(max 200 words)

[1] C. Zhang and P. Heiselberg, “Diffuse ceiling ventilation,” REHVA J., no. Special Issue Nordic Technology, pp. 78–82, 2019.

[2] C. Zhang, T. Yu, P. Heiselberg, M. Pominaowski, and P. Nielsen, “Diffuse Ceiling Ventilation: Design Guide,” DCE Techincal Rep., no. 27, 2016.

[3] A. D. Lemaire et al., “Room air and contaminant flow, evaluation of computational methods, subtask-1 Summary Report,” IEA Annex 20 Air Flow Patterns within Build., p. 82, 1993.

[4] P. V. Nielsen, “Analysis and Design of Room Air Distribution Systems,” HVAC&R Res., vol. 13, no. 6, pp. 987–997, 2007.



13:12 - 13:18

Developing thermal comfort maps for naturally ventilated spaces

Vardan Soi1, Swati Puchalapalli2, Rashmin M. Damle3

1Masters in Technology, Building Energy Performance (MTech BEP), CEPT University; 2Terraviridis; 3CEPT University

Aim and Approach

(max 200 words)

This paper presents an alternative methodology to calculate and visualize operative temperature (Top) for naturally ventilated (NV) spaces. It helps calculate Top at multiple points in space and time. The methodology calculates three environmental variables namely air-temperature (Tair), solar adjusted mean radiant temperature (Tmrt) & air-velocity (Vair) to determine thermal comfort. The methodology of the calculation can be divided into two parts. The first part relies on thermal simulation to obtain Tair and surface temperatures to calculate Tmrt. The second part relies on a simplified CFD simulation to obtain Vair. The weather data is binned for wind direction to optimize the number of CFD runs. The proposed method limits itself to iso-thermal airflow hence, accounts only for wind assisted ventilation.

The data from CFD & thermal Simulation is integrated with other calculation variables such as view factor & effective radiant field (ERF) to derive Tair, Tmrt & Vair spatio-temporally. Top across the thermal zone is calculated for grid points to generate point-in-time thermal plots. Further, Top across all the data points in space is translated into a spatio-temporal representation for a given set of thermal comfort acceptability criteria which indicates the percentage of times a grid point meets the comfort condition.

Scientific Innovation and Relevance

(max 200 words)

The literature review shows that Top has been calculated both spatially & temporally earlier (Mackie2015,Herkel1999,Marino2018,Webb2006), however with only two comfort variables (Tair, Tmrt) and for air-conditioned spaces. Further, several Studies plot Top for NV spaces, but are either point-in-time or space and do not capture impact of Vair on Top (jakubiec2019,Levitt2013). Vair distribution is one of the major factors behind thermal non-uniformity in NV spaces and Indoor thermal comfort is influenced greatly by airflow behaviour (Gan1994,Fulpagare2013). Thus, this research attempts to integrate three comfort parameters and captures thermal diversity in an indoor NV space both spatially & temporally.

NV is one of the most relevant passive strategies not just from the viewpoint of energy savings but also from the perspective of health, comfort & well-being (Jones1999). Spatial non-uniformity & lack of air movement has been the top reasons for thermal dissatisfaction in naturally ventilated scenarios. (Brager&Baker2009) Even if thermal comfort acceptability range for NV is wider, understanding the spatio-temporal characteristics of Top would help to minimize thermal non-uniformity and maximise comfort across the year. Thus, the proposed methodology could provide ‘schematic design stage’ support to designers helping them understand architectural dimensions of thermal comfort and thereby make informed design decisions.

Preliminary Results and Conclusions

(max 200 words)

A lecture room of an institutional building in Hyderabad, India has been selected to develop the methodology. Preliminary results indicate that the proposed methodology captures thermal non-uniformity in the space due to spatio-temporal variation of Tair, Tmrt & Vair. For instance, on a typical summer day (2ndMay,11am), Tair=37oC, Tmrt shows the impact of the high surface temperature of the exposed south & east walls. The wind speed (3.2ms-1) & direction (236o) for this timestep corresponds to CFD results of bin 12. The directional impact of Vair distribution counters the high Tmrt in the south & core zones thereby, reducing Top in these grid points. Similarly, Top was obtained at spatial resolution across all points-in-time and conditional statements were scripted to assign credit ‘1’ when Top<30oC (IMAC, NV) else ‘0’. These values for every grid point were averaged across the temporal range to obtain a spatio-temporal map which indicates percentage of time when the grid point is comfortable.

Thus, the proposed methodology can capture the impact of geometric implications along with the thermal properties of materials into a meaningful spatiotemporal interpretation of indoor thermal comfort, enabling designers in making informed design decisions ranging from façade to interiors and energy to comfort.

Main References

(max 200 words)

Mackie, C.(2015). Pan Climatic.

Herkel, Sebastian, Frank Schöffel, J.D.(1999). Interactive Three-Dimensional Visualization of Thermal Comfort.

Webb, A. L.(2013). Mapping comfort: An analysis method for understanding diversity in the thermal environment. Proceedings of BS 2013: 13th Conference of the International Building Performance Simulation Association,1642–1648.

Marino, C., Nucara, A., & Pietrafesa, M. (2015). Mapping of the indoor comfort conditions considering the effect of solar radiation.Solar Energy,113,63–77.

Jakubiec, J. A., Doelling, M. C., & Heckmann, O.(2017). A Spatial and Temporal Framework for Analysing Daylight, Comfort, Energy and Beyond in Conceptual Building Design. 15th IBPSA Conference, (January)

Levitt, B., Ubbelohde, M. S., Loisos, G., & Brown, N. (2013). Thermal Autonomy as Metric and Design Process. Building Lasting Change2013.

Gan, G. (1994). Numerical Method for a Full Assessment of Indoor Thermal Comfort. Indoor Air

Fulpagare, Y., & Agrawal, N. (2013). Experimental Investigation on Room Ait Flow Pattern & Thermal Comfort Quantification. International Journal of Engineering Sciences & Emerging Technologies,IJESET,6(1),120–132.

Jones, A. P. (1999). Indoor air quality and health. Atmospheric Environment, 1(C), 57–115.

ISO 7726: Ergonomic of the thermal environment - Instruments for measuring physical quantities.

Brager, G., & Baker, L. (2009). Occupant satisfaction in mixed-mode buildings. Building Research and Information,37(4),369–380.



13:18 - 13:24

Multi-objective optimisation of Indian Jaali fenestration system for visual, thermal and perceptual performance using computational methods

Afshan Rehman, Amulya Surapaneni

Carnegie Mellon University, United States of America

Aim and Approach

(max 200 words)

Jaali is a term used for perforated screens with floral or geometric patterns native to Indo-Islamic architecture. Historically, it has been used as an effective way in providing shade and privacy for building occupants in hot arid and hot humid climates. By changing the depth and the size of apertures of the Jaalis, one can reduce glare, solar insolation and achieve unobstructed views. Although individual studies on the impact of Jaalis on visual comfort and thermal comfort exist, no research currently examines how Jaali patterns affect both visual and thermal comfort at the same time. This paper introduces an experimental study to evaluate these concepts by replacing a glass facade of a modern library located in Delhi, India with a Jaali screen. A qualitative sample study was conducted for the library hall using six Jaali screens to ascertain the Jaali pattern that best improves the quality of light in the library hall. The most preferred Jaali pattern from the survey was then studied to quantitatively assess its visual and thermal properties. To determine the optimum aperture size and depth of the Jaalis, daylight metrics such as ASE and sDA, and thermal metrics such as indoor solar radiation were used.

Scientific Innovation and Relevance

(max 200 words)

People spend 90% of their time indoors and improving the indoor environmental quality increases the well-being and productivity of the occupants. For this, it is important to improve indoor environments quantitatively and qualitatively.

Jaali, an innovative latticed screen of ancient Indian architecture, affects both visual and thermal quality of a space. This paper introduces an experimental study that analyses the effect of shadows created by these Jaali patterns perceptually. Qualitative studies were used to analyse the perceptual performance of these patterns using surveys. Quantitative study was used to examine the effect of this Jaali pattern on both visual and thermal comfort by using visual programming simulation environments. Innovations in building simulations have paved a way for optimizing these intricate Jaali patterns for daylight and thermal comfort. The solid to void ratio and depth of Jaali screens were optimized parametrically to produce well-lit, thermally comfortable and glare-free indoor spaces.

The paper highlights an important research methodology to generate an optimized innovative Jaali pattern that can be used by architects and building performance engineers to develop building screens that improve the visual and thermal quality of indoor spaces.

Preliminary Results and Conclusions

(max 200 words)

The first section of the results presents a survey, in which the respondents selected one preferred Jaali pattern. The subsequent sections show how the solid-void ratio and thickness of the this Jaali pattern was changed parametrically to arrive at a final optimised pattern that gives the best possible results for daylight and thermal analysis.

The simulation results showed that a deeper Jaali screen provided better indoor thermal performance by reducing the indoor solar radiation. However, the overarching aim of this research was to create a Jaali screen that satisfies both visual and thermal comfort. A 100mm deep screen was selected, as Jaali screens that are more than 100 mm deep were drastically reducing the spatial daylight. This paper generated a final Jaali screen of solid-void ratio of 70%-30% and a depth of 100mm using both qualitative and quantitative strategies. The result of the paper demonstrates that the solid-void ratio and depth of Jaali screens can be optimized to produce well-lit, thermally comfortable and glare-free indoor spaces. The paper highlights an important research methodology to generate an optimized Jaali pattern that can be used to develop building screens that improve the visual and thermal quality of indoors.

Main References

(max 200 words)

1. Batool, A. (2014). "Quantifying Environmental Performance of Jali Screen Facades for contemporary buildings in lahore, pakistan.” Available from ProQuest Dissertations & Thesis Global.

2. Sherif, A., Sabry, H., & Rakha, T. (2012). External perforated Solar Screens for daylighting in residential desert buildings: Identification of minimum perforation percentages. Solar Energy, 86(6), 1929–1940. https://doi.org/10.1016/j.solener.2012.02.029

3. Gandhi, D (2014). “Stone Jaali - Daylight Performance Analysis.” Available from CARBSE article series.

4. Abdullahi, Y., & Embi, M. R. B. (2013). Evolution of Islamic geometric patterns. Frontiers of Architectural Research, 2(2), 243–251. https://doi.org/10.1016/j.foar.2013.03.002

(2018, April 7). Retrieved from https://sites.psu.edu/perforatedscreendesigner/

(2019, October 25). Retrieved from https://fluidhandlingpro.com/bernoulli-equation-and-the-venturi-effect.

5. Hamdani, M. & Bekkouche, Sidi Mohammed El Amine & Benouaz, Tayeb & Belarbi, Rafik & Mohamed Kamal, Cherier. (2014). Minimization of indoor temperatures and total solar insolation by optimizing the building orientation in hot climate. Engineering Structures and Technologies. 6. 131-149. 10.3846/2029882X.2014.988756.

6. Kurma, Naga Viswatej. (2017). Analyzing Sun Angles of Solar Time Dial for Design of Building Envelope Components for the Region of Andhra Pradesh, India. International journal of Emerging Trends in Science and Technology. 03. 5018-5028. 10.18535/ijetst/v4i3.06.



13:24 - 13:30

Fine-grained measurement of the indoor built environment with robotic vacuum cleaners

Joseph McLaughlin1, Michal Young1, Siobhan Rockcastle1,2

1University of Oregon, United States of America; 2Baker Lighting Lab

Aim and Approach

(max 200 words)

This paper presents a method of measuring ambient conditions in the built environment with a fine spatial and temporal granularity using autonomous robot vacuum cleaners. Our method records the illuminance and temperature of a space with 10cm accuracy over sub-second time-steps. The result is a dense dataset of measurements, capturing features of the environment over both space and time.

The built environment exposes occupants to a range of variable lighting and thermal conditions that are inherently dynamic over space and time. Past studies on the effects of light and thermal variability reveal the impact that dynamic exposure to these attributes may have on occupant health, comfort, and satisfaction indoors (Kim et al., 2018; Danell et al., 2020). However, we still lack methods of collecting distributed data about environmental attributes and rely heavily on statically mounted sensors. To address the limitations of static sensors, recent trends have explored the use of wearables devices, which are useful in modeling the experiences of occupants within a space (Ulaganathan et al, 2019). Our approach is distinguished from these methods, employing a single sensor package to map the built environment with the fidelity necessary to model the interdynamics of the space itself.

Scientific Innovation and Relevance

(max 200 words)

We attached a small computer with illuminance and temperature sensors to the exterior of an autonomous vacuum. We then constructed an indoor positioning system using a network of ultra-wideband radio transceivers to locate the vacuum cleaner as it moves through the space (Zafari et al., 2019). Measurements are collated on a remote host, providing network access to a dataset that is uniquely high-fidelity over both space and time.

This method offers several distinct advantages over typical methods of static measurement. Namely, our method provides the fidelity to make narrowly-localized assessments throughout a space. Further, our method can reveal “blind spots” missed by static measurements that rely on a fixed mounting location. This is done inexpensively and portably, using a single sensor package and a commercially available robot vacuum.

Our method may prove its utility in both research and industry applications, where the temporal and spatial data of indoor environmental attributes could drive building control systems, monitor real-time comfort conditions, or assess the baseline performance of a building without the cost of a hard-wired sensor network. Lighting and HVAC systems that utilize real-time data to adjust building performance would benefit from the immediate and continuous feedback that our method provides.

Preliminary Results and Conclusions

(max 200 words)

We performed an initial study of our method, recording 30,000 illuminance measurements over the course of 8 hours in an approximately 44m2 residential living space. On hourly intervals, the autonomous vacuum cleaner navigated the space for 30 minutes while measurements were taken from an on-board computer. Initial evaluation confirms the highly variable characteristics of illuminance measurements over space and time. The results further illustrate several intricate interactions within the space such as the effects of tall objects obstructing the path of daylight throughout the day. Our full-length paper will present the hardware and software components of our method as well as an expanded set of pilot results to demonstrate how the ambient dynamics of the built environment affect occupants on a uniquely local scale.

Main References

(max 200 words)

Ulaganathan, S., Read, S. A., Collins, M. J., & Vincent, S. J. “Influence of Seasons upon Personal Light Exposure and Longitudinal Axial Length Changes in Young Adults.” Acta Ophthalmologica, vol. 97, no. 2, 2019, pp. e256–65. Wiley Online Library, doi: 10.1111/aos.13904.

Kim, J., Schiavon, S., Brager, G. “Personal comfort models – A new paradigm in thermal comfort for occupant-centric environmental control.” Building and Environment, vol. 132, 2018, pp. 114-124,

Dannel, M., Amundadottir, M., Rockcastle, S. “Evaluating Temporal and Spatial Light Exposure Profiles for Typical Building Occupants. “ SimAUD 2020, Vienna Virtual Conference, May 25 – 27, 2020

F. Zafari, A. Gkelias and K. K. Leung, "A Survey of Indoor Localization Systems and Technologies," in IEEE Communications Surveys & Tutorials, vol. 21, no. 3, pp. 2568-2599, 2019



13:30 - 13:36

Investigating the relationship between interpretability and performance for optimal rule-based control

Eikichi Ono1,2, Kuniaki Mihara2, Takamasa Hasama2, Yuichi Takemasa2, Bertrand Lasternas1, Adrian Chong1

1National University of Singapore, Singapore; 2Kajima Technical Research Institute Singapore, Singapore

Aim and Approach

(max 200 words)

Recently, optimal controls such as model predictive control, or MPC, have become a hot and popular research topic. However, there are some hurdles for their application such as cost, reliability, tuning, maintenance, warranty and liability. On the other hand, some researches try to simplify optimal control algorithm based on rigorous optimization results. Robillart et al. (2018) have developed a regression model based on the optimization result of dynamic programming to reduce calculation cost. Drgoňa et al. (2018) have tried to approximate an optimization result of MPC by two learning method, regression tree (RT) and time delay neural network (TDNN). They point out that a RT model can be easily transformed to a rule-based control, but has some disadvantages such as accuracy and model complexity, compared to more complex algorithms like TDNN. However, there is no research that intends to optimize rules of rule-based controls in terms of control design support. Therefore, this research aims to develop an optimal rule generation method using machine learning techniques based on optimization results according to the structure of rule-based control logics.

Scientific Innovation and Relevance

(max 200 words)

Regression can be a solution for simplification of optimal controls as Robillart et al. (2018) studied, but complex regression models are not suitable for rule-based controls. The idea of Drgoňa et al. (2018), using regression tree, may be good because it has a similar structure to rule-based control logics. However, they consider only binary decisions in the RT model. Similarly, May-Ostendorp et al. (2011) and Domahidi et al. (2014) have tried to simplify control logics based on optimization results, but they deal with only binary decisions. Because including only binary decisions leads to high complexity, redundancy, and less accuracy of logics, it should be better to study the structure of the regression tree in reference to actual rule-based controls. Thus, we try to improve the structure of the tree by mixing binary decisions and linear functions at its nodes and leaves, leading to more practical rules in terms of their accuracy and interpretability. Since the optimal rule-based control consists of simple logics, it has some advantages compared to complex control algorithms like MPC; e.g. it is easily understandable and adjustable for engineers and can be widely installed in not only new buildings but also existing buildings.

Preliminary Results and Conclusions

(max 200 words)

We conduct a simulation case study which aims to maximize both thermal comfort and energy performance for an office space air-conditioned by a dedicated outdoor air system with ceiling fans (Mihara et al., 2019) considering thermal preference distribution of occupants. Since the system can control two variables of zone air temperature and air velocity, and occupants have different thermal sensation even in the same thermal condition, this optimization problem can be complicated and it is not easy to optimize rule-based control design. Firstly, the setpoints of zone air temperature, supply air temperature and ceiling fan speed are optimized by a genetic algorithm. The result shows that the optimal operation using ceiling fans and considering individual thermal preference can significantly increase thermal comfort of occupants and also reduce energy consumption, but cannot be easily interpretable for control design. Secondly, as a result of optimal rule generation by the improved regression tree model based on the optimization result, it is found that the model can generate more accurate and interpretable rules than the original regression tree model.

Main References

(max 200 words)

[1] Domahidi, A., Ullmann, F., Morari, M. and Jones, C. N. (2014). Learning decision rules for energy efficient building control. Journal of Process Control, 24, 763–772.

[2] Drgoňa, J., Picard, D., Kvasnica, M. and Helsen, L. (2018). Approximate model predictive building control via machine learning. Applied Energy, 218, 199–216.

[3] May-Ostendorp, P., Henze, G. P., Corbin, C. D., Rajagopalan, B. and Felsmann, C. (2011). Model-predictive control of mixed-mode buildings with rule extraction. Building and Environment, 46, 428-437.

[4] Mihara, K., Sekhar, C., Takemasa, Y., Lasternas, B. and Tham, K. W. (2019). Thermal comfort and energy performance of a dedicated outdoor air system with ceiling fans in hot and humid climate. Energy & Buildings, 203, 109448.

[5] Robillart, M., Schalbart, P. and Peuportier, B. (2018). Derivation of simplified control rules from an optimal strategy for electric heating in a residential building. Journal of Building Performance Simulation, Vol. 11, No. 3, 294–308.



13:36 - 13:42

Performance of aerogels as thermal insulation materials for buildings in tropical climates

Aminu Wali Bashir, Eliane Hayashi Suzuki, Joao Roberto Diego Petreche, Brenda Chaves Coelho Leite

Universidade de São Paulo, São Paulo, Brazil

Aim and Approach

(max 200 words)

This study aims to examine the influence and suitability of inserting aerogels on wall surfaces of buildings in the tropical regions with an emphasis on energy consumption reduction and thermal comfort improvement.

Building modeling and computational energy simulations were conducted on tropical climates of Lagos, Nigeria, and Belem-Para, Brazil. The selected locations have similar annual weather conditions, and the architecture of buildings is also similar. A single design was selected to represent the two locations: a residential building with thermal zones distributed on two floors.

As the local materials used for construction vary significantly, the simulation models were based on the materials commonly used in each location and with aerogel material inserted on the external wall surfaces of the buildings. The results of the simulations were compared to effectively conclude on the significance of the insulation material in each location. The average temperatures are almost constant throughout the year in both locations, therefore, simulations were run for a typical design day in summer. Zones’ mean air & operative temperatures and air relative humidity values were measured and compared to the standard recommended range. The analysis of the results was carried out based on each floor.

Scientific Innovation and Relevance

(max 200 words)

The two selected locations are both in coastal regions, with moderately high temperatures, high relative humidity, and high rainfall virtually throughout the year. The use of HVAC systems for cooling of buildings in these locations covers a large percentage of the total energy consumption. However, energy efficiency measures through the adoption of insulation materials are recognized to be tools that could affect the heat gain and/or loss within buildings and reduce energy demand. Aerogel has then been identified to be the most promising solution when insulation is required due to its very low thermal conductivity feature [1], [2], hence its selection for this study.

There are various publications on the application of aerogels in buildings [3], [4], [5], [6], but none considered analyzing its significance through modeling and building energy simulations and its consequences on tropical climates. Thus, this study intends to lay out a foundation for this type of methodology which, if proven to be significant, can serve as a base reference for insulating buildings in tropical climates (which covers almost 40% of the global landmass). Also, these strategies could improve thermal comfort in the buildings, especially in locations where energy supply is not constant.

Preliminary Results and Conclusions

(max 200 words)

• Simulation with conventional materials

The measured mean air and operative temperatures for a typical summer day in the two selected locations were similar and could be comparable. Also, the values were above the recommended range in both locations especially for thermal zones on the first floor, basically due to the effect of solar radiation. The corresponding air relative humidity values recorded in Lagos were within the recommended range while the values for Belém were above the range virtually throughout the day.

• Simulations with aerogel material

The insertion of the insulation material appeared to have more significance in Belém than in Lagos. A decrease of 2.1% on first floor zones and up to 6.1% on ground floor zones was recorded in the measured temperatures in Belém, while for Lagos, the decrease was between 0.6% for first floor zones to 1.3% for ground floor zones. However, the decrease in the measured temperatures slightly increased the corresponding air relative humidity.

The insertion of Aerogel on wall surfaces of the models showed the potential of reducing the indoor temperatures in both locations. This means there will be less demand for mechanical cooling and at the same time improves thermal comfort.

Main References

(max 200 words)

[1]. Allouhi, A., El Fouih, Y., Kousksou, T., Jamil, A., Zeraouli, Y., & Mourad, Y. (2015). Energy consumption and efficiency in buildings: Current status and future trends. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2015.05.139

[2]. Jelle, B. P. (2011). Traditional, state-of-the-art, and future thermal building insulation materials and solutions - Properties, requirements, and possibilities. Energy and Buildings, 43(10), 2549–2563. https://doi.org/10.1016/j.enbuild.2011.05.015

[3]. Baetens, R., Jelle, B. P., & Gustavsen, A. (2011). Review: Aerogel insulation for building applications: A state-of-the-art review. Energy & Buildings. https://doi.org/10.1016/j.enbuild.2010.12.012

[4]. Cuce, E., Cuce, P. M., Wood, C. J., & Riffat, S. B. (2014). Toward aerogel based thermal superinsulation in buildings: A comprehensive review. Renewable and Sustainable Energy Reviews. https://doi.org/10.1016/j.rser.2014.03.017

[5]. Roya, H. N., Umberto Berardi, Nosrati, R. H., & Berardi, U. (2018). Hygrothermal characteristics of aerogel-enhanced insulating materials under different humidity and temperature conditions. Energy and Buildings, 158, 698–711. https://doi.org/10.1016/j.enbuild.2017.09.079

[6]. Riffat, S. B., & Qiu, G. (2013). A review of state-of-the-art aerogel applications in buildings. International Journal of Low-Carbon Technologies. https://doi.org/10.1093/ijlct/cts001



13:42 - 13:48

A combined CFD-based genetic algorithm and human body thermoregulation model for designing the indoor thermal environment

Wei Liu1, Yu Xue2, Dayi Lai3

1Division of Sustainable Buildings, Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, Brinellvägen 23, Stockholm, 100 44, Sweden; 2School of Civil Engineering, Dalian University of Technology, Dalian 116024, China; 3Department of Architecture, School of Design, Shanghai Jiao Tong University, Shanghai 200240, China

Aim and Approach

(max 200 words)

A thermally comfortable indoor environment is critical for ensuring the health and productivity of the occupants (Schellen et al., 2010). This study aims to develop a combined CFD-based genetic algorithm and human body thermoregulation model for the inverse design of indoor thermal environment. This investigation developed the CFD solver in OpenFOAM (Jasak et al., 2007), the genetic algorithm by GenOpt (Xue et al., 2019), and the human body thermoregulation model in Matlab (Lai and Chen, 2016). A shell file was used to run those three parts in need automatically. The developed model was validated by the measured human skin temperature from literature. The model was further applied to design the thermal environments in an office with displacement ventilation and an aircraft cabin with mixed ventilation for demonstration.

Scientific Innovation and Relevance

(max 200 words)

This study implemented a new way for evaluating the thermal comfort level in the inverse design of indoor environment. On the one hand, the developed model considered the heterogeneous thermal environments, such as vertical air temperature gradient, non-uniform radiation, and spatially different air distribution, which improves the accuracy in estimating the thermal comfort level. On the other hand, the coupling would not only overcome the inaccurate CFD prediction due to fixed surface temperature of the occupants, but also lead to reliable estimation of the occupants' thermal comfort level.

Preliminary Results and Conclusions

(max 200 words)

After validating the performance of the human thermoregulation model coupled with CFD in predicting skin temperature, we used the model to inverse design the indoor thermal environment in an office and an aircraft cabin. In the office case with displacement ventilation, the thermal comfort was maximized when the air supply air temperature and velocity was 25 oC, and 0.08 m/s. While in the aircraft cabin, the objective function was the minimum when the slot diffuser supplied 26 oC of air by 0.32 m/s. Coupling thermoregulation model with CFD inverse design provides a more detailed way to optimize the indoor thermal environment, and at the same time, local thermal discomfort can be reduced.

Main References

(max 200 words)

Jasak, H., Jemcov, A., Tukovic, Z., et al., 2007. Openfoam: A c++ library for complex physics simulations, in: International workshop on coupled methods in numerical dynamics, IUC Dubrovnik Croatia. pp. 1–20.

Lai, D., Chen, Q., 2016. A two-dimensional model for calculating heat transfer in the human body in a transient and non-uniform thermal environment. Energy and Buildings 118, 114–122.

Schellen, L., van Marken Lichtenbelt, W.D., Loomans, M.G., Toftum, J., De Wit, M.H., 2010. Differences between young adults and elderly in thermal comfort, productivity, and thermal physiology in response to a moderate temperature drift and a steady-state condition. Indoor air 20, 273–283.

Xue, Y., Liu, W., Wang, Q., Bu, F., 2019. Development of an integrated approach for the inverse design of built environment by a fast fluid dynamicsbased generic algorithm. Building and Environment 160, 106205.



13:48 - 13:54

Simulation of COVID-19 ultraviolet disinfection using coupled ray tracing and CFD

Nathaniel Jones1, Paul Lynch2, Joseph Hewlings1, Justin Boyd2, Ryan Seffinger1, Dan Lister2, Renee Thomas1

1Arup, United States of America; 2Arup, United Kingdom

Aim and Approach

(max 200 words)

Ultraviolet Germicidal Irradiance (UVGI) is the effective technique of employing ultraviolet radiant energy to inactivate (and render non-infectious) disease causing bacteria, mold spores, fungi and viruses. In the context of COVID-19, UVGI may be employed in the upper unoccupied zone of a room to reduce viral concentrations by four orders of magnitude. However, the effect on air in the occupied zone is dependent on mixing via air exchange and temperature gradients. We present a computational fluid dynamics (CFD) based approach to model disinfection of respiratory droplets and aerosolized pathogens in the occupied zone. Our CFD model informs the specification and placement of UVGI lamps to mitigate risk of infection. We use the CFD model to validate some simple calculation methods for UVGI effectiveness (including those by Rudnick & First and Beggs & Sleigh) which are then integrated with the Wells-Riley model of airborne infection risk to assess the relative benefit of UVGI with and against other measures. While the world awaits a cure, this method allows us to make facilities safer and thus prevent the spread of COVID-19 and all subsequent threats from respiratory virus outbreaks.

Scientific Innovation and Relevance

(max 200 words)

The innovation in our method is the use of ray tracing and CFD to model the interaction of UVGI energy with pathogens in the unoccupied space and its effect on the occupied zone below. Experimentally, this technique was first shown in 1892 to be effective in destroying Bacillus anthracis – the bacteria that causes anthrax. UVGI technology has been used extensively and successfully in the hospital and healthcare setting. Using our simulation workflow, we can expand UVGI disinfection to the workplace broadly, in educational facilities, entertainment venues, transportation hubs – anywhere large groups of people transit or gather that have been affected by COVID-19. We can combine CFD with less resource-intensive tools to tailor the level of analysis as appropriate – from rapid screening of infection control measures to fine-tuning of UVGI system design.

Preliminary Results and Conclusions

(max 200 words)

We demonstrate a tool that provides real-time calculation of UVGI dosing using the visual programming language Grasshopper within the Rhinoceros 3D environment, and an extension to this that exports UVGI fluence in an air volume to CFD. The CFD results are validated against the Wells-Riley, Rudnick & First and Beggs & Sleigh equations for simple geometries, but CFD also allows analysis of complex spaces, including those with partitions or obstructions that limit the mixing of air.

Main References

(max 200 words)

Beggs, Clive B. & Sleigh, Andrew. “A quantitative method for evaluating the germicidal effect of upper room UV fields.” Journal of Aerosol Science 33 (2002) 1681-1699.

Buonanno, Giorgio, Stabile, Luca and Morawska, Lidia. “Estimation of airborne viral emission: quanta emission rate of SARS-CoV-2 for infection risk assessment.” Environment International 141 (2020) 105794.

Malayeri, Adel Haji, et al. "Fluence (UV dose) required to achieve incremental log inactivation of bacteria, protozoa, viruses and algae." IUVA News 18.3 (2016): 4-6.

Noakes, C. J., C. B. Beggs, and P. A. Sleigh. "Modelling the Performance of Upper Room Ultraviolet Germicidal Irradiation Devices in Ventilated Rooms: Comparison of Analytical and CFD Methods." Indoor and Built Environment 13.6 (2004): 477-488.

Riley, Richard L., and Solbert Permutt. "Room air disinfection by ultraviolet irradiation of upper air." Archives of Environmental Health: An International Journal 22.2 (1971): 208-219.

Riley, Richard L., Solbert Permutt, and James E. Kaufman. "Convection, air mixing, and ultraviolet air disinfection in rooms." Archives of Environmental Health: An International Journal 22.2 (1971): 200-207.

Rudnick, Stephen N., and Melvin W. First. "Fundamental factors affecting upper-room ultraviolet germicidal irradiation—Part II. Predicting effectiveness." Journal of Occupational and Environmental Hygiene 4.5 (2007): 352-362.



13:54 - 14:00

Radiation control optimization for dynamic glazing in building façades in subtropical climate

Eliane Hayashi Suzuki, Racine Tadeu Araujo Prado, Brenda Chaves Coelho Leite

Universidade de Sao Paulo, Brazil

Aim and Approach

(max 200 words)

This study aims to discuss the participation of the window as responsible for room air temperature increase along the day in subtropical humid climate. For this, a high insulated glazing system was proposed for offices windows in order to investigate compositions with low U-factor. Previous study regarding Brazilian climates [1] showed that insulated glass unit (IGU) might increase energy consumption in office buildings. In this study, dynamic insulated glass unit with electrochromic layer was considered. Although chromogenic glazing technology seems to be more adequate for cold climates, there is a discussion whether it is appropriated for hot climates either. Simulations were carried out for a small office room in Sao Paulo/Brazil considering automation controls currently available for electrochromic glazing, based on occupancy and outdoor air dry bulb temperature, for example. Also, other parameters were tested for construction index control, being more adequate for hot climates. Rhinoceros, Grasshopper with Ladybug and Honeybee plugins, EnergyPlus 9.3 and Parametric PreProcessor tools were considered in modeling and simulation process. Analysis were conducted in terms of adaptive comfort based on ISO 7730 [2] and ASHRAE 55 standards [3], and energy consumption criteria.

Scientific Innovation and Relevance

(max 200 words)

Chromogenic glazing performance has been exhaustively studied in temperate climates in order to face rigorous winter and great temperature difference along the year. In this research, an evaluation of electrochromic insulated glass unit for subtropical humid climate is proposed. In electrochromic technology there is a reversible change in materials optical properties related to ionization process, according to environmental parameters [4]. [5] had found that electrochromic glazing allows passive heating during the winter and solar gain reduction in the summer, saving energy up to 48%. In the case of Sao Paulo/Brazil, demand for cooling is higher than for heating, because even when the outside air temperature is low, office activities’ internal thermal load is enough to heat the environment. So, in most of the time in the winter, there is cooling demand rather than heating. For this reason, electrochromic would be useful for radiation control in the summer, when it is necessary to block diffuse and beam incident solar radiation. As electrochromic glazing is not commercialized in Brazil, it should be studied the types of existing controllers in North America [6] and Europe, and how they apply in the subtropics.

Preliminary Results and Conclusions

(max 200 words)

In hot climates, where irradiance level is relatively high along the year, radiation control of windows plays an important role for thermal comfort and energy efficiency. Results showed that there is potential in using electrochromic glazing in subtropical climate, since there would be a combination of natural ventilation coupled with HVAC system. Window is usually the weaker device for thermal performance in the building envelope when compared to other construction elements. In this way, electrochromic glazing may reduce energy transmission through the window and decrease envelope contribution to thermal load in hot days. However, it might happen an undesired passive heating of the space as the windows have high insulation level, thus increasing air supply total cooling energy from HVAC system. Data analysis along the year showed better combinations of glazing status control for thermal performance, e.g. total incident radiation in windows surface and seasonal schedule considering initial index – darker or lighter state. This case can also be applied for residential rooms, which become home office in covid-19 pandemic period and have the same work demands for comfortable and healthy places.

Main References

(max 200 words)

[1] PINTO, M. M.; WESTPHAL, F. S. Energy performance of office buildings in Brazil using insulated glass units. 16th IBPSA International Conference and Exhibition. In: Proceedings… Rome: IBPSA, 2019.

[2] INTERNATIONAL STANDARD ORGANIZATION. ISO 7730: Ergonomics of the thermal environment - Analytical determination and interpretation of thermal comfort using calculation of the PMV and PPD indices and local thermal comfort criteria. Geneva: International Organization for Standardization, 2005.

[3] AMERICAN SOCIETY OF HEATING, REFRIGERATING AND AIR-CONDITIONING ENGINEERS. ASHRAE Standard 55: Thermal Environmental Conditions for Human Occupancy. Atlanta: ASHRAE, 2013.

[4] BAETENS, R.; JELLE, B. P.; GUSTAVSEN, A. Properties, requirements and possibilities of smart windows for dynamic daylight and solar energy control in buildings: A state-of-the-art review. Solar Energy Materials and Solar Cells, v. 94, n. 2, p. 87–105, 2010.

[5] LEE, E. S.; CLAYBAUGH, E. S.; LAFRANCE, M. End user impacts of automated electrochromic windows in a pilot retrofit application. Energy and Buildings, v. 47, p. 267–284, 2012.

[6] DUSSAULT, J. M.; GOSSELIN, L. Office buildings with electrochromic windows: A sensitivity analysis of design parameters on energy performance, and thermal and visual comfort. Energy and Buildings, v. 153, p. 50–62, 2017.



14:00 - 14:06

Influence of interventions against spread of COVID-19 on noise levels in student restaurant

Lukáš Zelem1, Vojtech Chmelík2, Monika Rychtáriková3

1STU Bratislava, Faculty of Civil Engineering, Department of Architecture; 2STU Bratislava, Faculty of Civil Engineering, Department of Architecture; 3KU Leuven, Faculty of Architecture,

Aim and Approach

(max 200 words)

One of the main interventions against the spread of COVID-19 is so called social distancing, which has rather large consequence on activities held in the building interior. The direct impact can be seen in the limitations of the number of people present in an enclosed space at the same time in order to fulfil the necessary distance between persons.

However, these rather unpleasant restrictions with dramatical impact on functioning of the so-called HORECA (hotel-restaurant-café) services, turned out to have also a positive impact on the indoor acoustic comfort. The main difference can be seen in the decreased noise levels in restaurants, cafes and bars.

Scientific Innovation and Relevance

(max 200 words)

Smaller number of talking people present inside a room means also lower noise levels. The fact that human vocal output depends on a situation and that people adopt their voice power to the surrounding noise (so called Lombard effect) can (in moderately occupied restaurants) result in even lower sound levels than one could presume [1]. This article focuses on the prediction of noise levels produced by talking crowd of people in the student restaurant at Civil Engineering faculty STU Bratislava. The ground dimensions of cantina are 21 × 23 m, height of ceiling 3.8 m and volume 1775 m3. Standard capacity of student restaurant (before epidemy of COVID-19) is 280 sitting places. The two situations are compared: (1) typical situation before the epidemy of COVID-19 with maximum number of people present in this room and (2) situation with maximum allowed number of people present, so that the requirements of Slovak government against the spread of COVID-19 [1] would be fulfilled. A prediction of the sound pressure level is performed by means of Odeon software, using adaptation algorithm for Lombard effect.

Preliminary Results and Conclusions

(max 200 words)

Decreasing the number of people present in a room means also decreasing of sound sources and therefore noise levels. But in case of restriction due to spread of COVID-19 it doesn’t mean only fewer people in enclosed space, but also larger distance between groups of people with maximum of two people at one table as well. It could lead to higher number of speaking persons in one moment , but it might avoid that Lombard effect would take place.

Main References

(max 200 words)

[1] J. H. Rindel, „Verbal communication and noise in eating establishments,“ Applied Acoustics, %1. vyd.71, pp. 1156-1161, 2010.

[2] UVZ, „Úrad verejného zdravotníctva Slovenskej republiky,“ Slovenská republika, 14. july 2020. [Online]. Available: http://www.uvzsr.sk/index.php?option=com_content&view=article&id=4132:covid-19-zavery-z-ustredneho-krizoveho-tabu-sr-povinnos-nosenia-ruok-na-verejnosti-zatvorenie-obchodov-v-nedeu-vyleneny-nakupny-as-pre-seniorov-a-pod&catid=250:koronavirus-2019-ncov&Ite. [Cit. 27 júl 2020].

[3] L. Zelem, V. Chmelík, M. Rychtáriková a C. Glorieux, „Analysis of the acoustic behavior of people in a restaurant,“ rev. EuroRegio, Porto, 2016.

 
14:40 - 16:10Session W3.1: Practice and industry related case studies
Location: Concert Hall - Forum 6
Session Chair: Jeffrey Spitler, Oklahoma State University
Session Chair: Anna Bortkiewicz, Daikin
Concert Hall - Forum 6 
 
14:40 - 14:58

Buoyancy-driven ventilation in a real operational building: Uncertainty quantification of the discharge coefficient

Lup Wai Chew, Chen Chen, Catherine Gorlé

Stanford University, United States of America

Aim and Approach

(max 200 words)

The ventilation rate across an opening is characterized by the still-air discharge coefficient, Cd, which can be estimated experimentally. Once determined, Cd is often specified as a constant in empirical models used for the designs of natural ventilation systems. However, under realistic operating conditions, the value of Cd can be affected by deviations from the still-air conditions in the local flow (Etheridge, 2011). As a result, the assumption of a constant value can introduce errors in estimating the natural ventilation rate, especially when considering complex buildings.

We aim to study uncertainty in Cd in a real operational building with a buoyancy-driven ventilation system using large eddy simulations (LES) in OpenFOAM. We focus on modeling the Y2E2 building at Stanford University, as measurements of indoor and outdoor temperatures are available (Lamberti & Gorlé, 2018). The LES model is first validated with measurements collected in the building. The validated model is then used to simulate nine scenarios with different initial and boundary conditions for the indoor and outdoor temperature. The results are post-processed to determine the uncertainty in Cd for the different windows, and this uncertainty is propagated through an empirical model to quantify the resulting uncertainty in the ventilation rate.

Scientific Innovation and Relevance

(max 200 words)

Buildings made up 32% of the total global energy consumption in 2010 (IPCC, 2014). In tropical countries such as India, air conditioning can account for more than half the energy consumption of buildings (Berardi, 2015). Natural ventilation does not consume energy and offers mitigation to the unsustainable energy consumption in the building sector. However, the design of natural ventilation systems is extremely challenging with many unpredictable parameters including the outdoor conditions and occupant behavior (Chen, 2009; Etheridge, 2011). The design process is often simplified by assuming a constant Cd for openings (Etheridge, 2011), although Cd is expected to vary especially in complex buildings. Our case study of a real operational building quantifies the errors introduced by the constant Cd assumption when estimating the natural ventilation rate, especially with unsteady outdoor conditions. The finding thus suggests that incorporating a non-constant Cd, informed by LES, can improve the design process of natural ventilation systems.

Preliminary Results and Conclusions

(max 200 words)

The LES model is built and meshed in the ANSYS Workbench package. The simulation domain consists of the target building and its surrounding. The outermost boundaries (2-3H away from the building in each direction, where H = 13 m is the building height) have zero-gauge-pressure boundary condition for pressure and zero-gradient boundary condition for all other parameters. The windows are not fully opened (i.e., at an inclined angle) and are therefore modeled as openings with a porous pressure jump to include the resistance due to the inclined angle. The building walls have no-slip and adiabatic boundary conditions. The floors and ceiling have no-slip and constant-temperature boundary conditions. Wall functions are employed to reduce the total number of grid points. The mesh has 2.6 million grid points, which is verified to have achieved mesh-independent results by comparing to the results obtained with a finer mesh of 8.6 million grid points. The simulated temperatures agree well with measurements. The next step is to use the validated model to simulate the nine cases, which are then used to quantify the uncertainty in Cd.

Main References

(max 200 words)

Berardi, U. (2015). Building energy consumption in US, EU, and BRIC countries. Procedia engineering, 118, 128-136.

Chen, Q. (2009). Ventilation performance prediction for buildings: A method overview and recent applications. Building and environment, 44(4), 848-858.

Etheridge, D. (2011). Natural ventilation of buildings: theory, measurement and design. John Wiley & Sons.

IPCC, Intergovernmental Panel on Climate Change (2014), Climate change 2014: Mitigation of climate change, Chapter 9: Buildings.

Lamberti, G., & Gorlé, C. (2018). Uncertainty quantification for modeling night-time ventilation in Stanford’s Y2E2 building. Energy and Buildings, 168, 319-330.



14:58 - 15:16

Impact of landscaping elements on pedestrian wind simulations using OpenFOAM

Rubina Ramponi1, Viet Le2, Jake Haskell3, Adam Brooks2

1Arup, Dublin, Ireland; 2Arup, New York, United States of America; 3Arup, Berlin, Germany

Aim and Approach

(max 200 words)

Modern cities have experienced for years a trend towards rapid urbanization and development of tall buildings to accommodate a growing population. The recent pandemic, however, has highlighted the impact of urbanization on the outdoor environment and the importance of well-designed outdoor spaces.

When looking at the user experience of the outdoors, wind has an important role in the perception of comfort. Numerical CFD simulations help designers to assess windiness around buildings and to identify areas that need mitigations. Testing the effectiveness of these different mitigation measures is a key component of pedestrian wind assessments, although modelling their aerodynamic properties in CFD is often a challenge.

This paper illustrates a case study where landscape is used to mitigate adverse wind conditions in a public space. CFD simulations are performed using the open-source software OpenFOAM and user-defined functions were implemented to describe the vegetation as a source of momentum and turbulence. A sensitivity study to the porosity of the trees is first carried out to identify suitable Leaf Area Density (LAD) values. Then, the sensitivity of the results to the use of turbulence sources, often ignored in commercial studies, is evaluated and discussed.

Scientific Innovation and Relevance

(max 200 words)

A number of literature studies discuss tree modelling using wind tunnel (Bitog et al., 2011; Gromke and Ruck, 2008; Manickathan et al., 2018) and CFD (Buccolieri et al., 2018; Gromke and Blocken, 2015; Mochida et al., 2008), where trees are generally represented as porous media and characterized by a drag coefficient (Cd) and a porosity index, such as the leaf area density (LAD).

Manickathan et al. (2018) recently published a comprehensive wind tunnel study that provides a better understanding of the tree aerodynamic properties and behavior when exposed to the wind/ This study supports further investigation in the accurate modelling of vegetation using numerical methods.

Most of commercial studies ignore the turbulence effect of vegetation and model trees only as a momentum source/sink using a default porosity model. This study illustrates an easy implementation of user-defined sources in OpenFOAM to account for both momentum and turbulence and illustrate the advantages of a more accurate modelling of vegetation for pedestrian level wind studies.

Preliminary Results and Conclusions

(max 200 words)

The study illustrates the benefits of landscaping to improve wind comfort in a public open space. The results show that foliage and planting effectively shelter key occupant areas, with a positive impact on the pedestrian wind comfort within the vicinity of the trees. An accurate representation of these mitigations is therefore important when carried out wind studies.

A sensitivity analysis of the LAD values was carried out and the impact of the LAD is less dramatic than expected. A LAD of 1.1 m²/m³ produces already a significant amount of wind shelter and the addition of further planting leads to diminishing returns. A LAD of 2.2 m²/m³ only reduces the local velocity at pedestrian level by a further 15% and also does not mitigate the issue of the strong shear flow around the corner of the building which also strongly impacts the pedestrian comfort at ground level. The results of the sensitivity analysis to the turbulence sources will discussed in the full paper.

Main References

(max 200 words)

Bitog, J.P., Lee, I.B., Hwang, H.S., Shin, M.H., Hong, S.W., Seo, I.H., Mostafa, E., Pang, Z., 2011. A wind tunnel study on aerodynamic porosity and windbreak drag. Forest Science and technology 7(1), 8–16.

Buccolieri, R., Santiago, J.-L., Rivas, E., Sanchez, B., 2018. Review on urban tree modelling in CFD simulations: Aerodynamic, deposition and thermal effects. Urban Forestry & Urban Greening 31, 212–220.

Gromke, C., Blocken, B., 2015. Influence of avenue-trees on air quality at the urban neighborhood scale. Part I: Quality assurance studies and turbulent Schmidt number analysis for RANS CFD simulations. Environmental Pollution 196, 214–223.

Gromke, C., Ruck, B., 2008. Aerodynamic modelling of trees for small-scale wind tunnel studies. Forestry (Lond) 81, 243–258.

Manickathan, L., Defraeye, T., Allegrini, J., Derome, D., Carmeliet, J., 2018. Comparative study of flow field and drag coefficient of model and small natural trees in a wind tunnel. Urban Forestry & Urban Greening 35, 230–239.

Mochida, A., Tabata, Y., Iwata, T., Yoshino, H., 2008. Examining tree canopy models for CFD prediction of wind environment at pedestrian level. Journal of Wind Engineering and Industrial Aerodynamics, 4th International Symposium on Computational Wind Engineering (CWE2006) 96, 1667–1677.



15:16 - 15:34

Full-scale validation of natural ventilation models in Stanford’s Y2E2 building

Chen Chen, Catherine Gorlé

Stanford University, United States of America

Aim and Approach

(max 200 words)

The objective of the present study is to accomplish full-scale validation of buoyancy-driven natural ventilation models for Stanford’s Y2E2 building. We use computational fluid dynamics (CFD) and uncertainty quantification (UQ) to identify optimal locations for temperature sensors under uncertain boundary and initial conditions. This will ensure that the measurements provide values representative of the volume-averaged temperature, while also characterizing spatial variability in the temperature field for validation of CFD results. The presentation will first introduce the set-up of CFD model, the characterization of the uncertain input parameters and the propagation method. Subsequently, we will present the results for the quantities of interest defined to select the optimal sensor locations. The results of the full-scale experiments will be presented together with a comparison to predictions obtained by the CFD model and a low-fidelity building thermal model.

Scientific Innovation and Relevance

(max 200 words)

Natural ventilation can significantly reduce building energy consumption, but the complexity of the governing flow and heat transfer phenomena and the variability in the boundary and operating conditions make robust design a challenging task. Efficient modeling strategies that can account for this complexity and uncertainty could provide essential information during the design process, but validation in full-scale buildings should be pursued to quantify their predictive capabilities. In a previous study, a multi-fidelity computational framework with UQ was proposed to predict the volume-averaged indoor air temperature during night-time ventilation in one of the atria of Stanford’s Y2E2 building. The framework combines a computationally efficient building thermal model to quantify uncertainty in the boundary and operating conditions with a more expensive CFD model to more accurately represent the complexity of the flow (Lamberti & Gorlé, 2018). Comparison of the results with building sensor measurements indicated that the sensor locations might result in data that is not be representative of the volume-averaged temperature; hence, a more careful experimental design is needed to support successful validation. The proposed method could more generally be used to design full-scale experiments for validation, and to decide on the location of building sensors used during operation.

Preliminary Results and Conclusions

(max 200 words)

For the CFD-based design of experiments, five dependent uncertain parameters are first characterized by fitting historical building measurements to beta distributions. Using a Nataf transformation, these dependent uncertain parameters are transformed into a set of independent random variables, which are propagated through the CFD model using a polynomial chaos approach. Three quantities of interest, which indicate whether a specific location is representative of the volume-averaged, minimum, or maximum temperature are defined. The mean and standard deviations of these quantities of interest are used to decide on the optimal sensor locations. On each floor, the volume-averaged temperature will be obtained by averaging data obtained from 5 sensors; measurements representative of the minimum and maximum temperatures will be obtained from additional sensors close to windows and in hallways between offices, respectively. The full-scale experiment is currently ongoing, and the results will be used to validate both the building thermal model and the CFD model predictions.

Main References

(max 200 words)

Lamberti, G., & Gorlé, C. (2018). Uncertainty quantification for modeling night-time ventilation in Stanford’s Y2E2 building. Energy and Buildings, 168, 319-330.



15:34 - 15:52

Whole-building energy simulation analysis and optimization of residential building equipped with air-duct system in three different regions

Arash Zarmehr, Joseph T. Kider .Jr

Institute for Simulation and Training, University of Central Florida, United States of America

Aim and Approach

(max 200 words)

Building-integrated photovoltaics (BIPV) systems, on the outer layer of a building structure, have the ability to reduce electricity and materials costs, as well as pollution, by taking advantage of renewable energy sources (sunlight and wind), and changes in thermal resistance. A BIPV ventilation air-gap system and its effects on heating and cooling loads are presented in this work. We use computational fluid dynamics to model, analyze, and compare BIPV air-gap and attic ventilation strategies and their impact on building energy performance. Results suggest an attic natural ventilation increase by 2.8 mph and a mean temperature decrease by 11.2%. One novel contribution of this work includes a BIPV attachment, that converts the air-gap into a miniature wind catcher to further improve building performance. This design improves upon traditional air-gap architectures by increasing natural air velocity while decreasing photovoltaic and attic temperatures.

Scientific Innovation and Relevance

(max 200 words)

The results of this study can introduce the benefits of using BIPV special designs to reduce the investment cost of using renewable energy and increase ROI for residential buildings. It can also be extended to commercial buildings. These benefits include increase productivity and efficiency of PV (which means more power production) and using natural ventilation to reduce building cooling and heating loads (which means less end-use consumption).

Preliminary Results and Conclusions

(max 200 words)

Primary results show the benefit of this air-duct BIPV system to increase airflow velocity under PV panels and then direct the high-velocity airflow to the attic. Results suggest an attic natural ventilation increase by 2.8 mph and a mean temperature decrease by 11.2%.

Main References

(max 200 words)

Zarmehr, A., and J. T. Kider, Jr. (2018). Modeling and simulation of parametric wind-catcher designs for natural ventilation in sustainable building skin architecture. Advanced Building Skins.

Gan, G. (2009). Effect of air gap on the performance of building-integrated photovoltaics. Energy 34 (7), 913–921.

Goverde, H., D. Goossens, J. Govaerts, F. Catthoor, K. Baert, J. Poortmans, and J. Driesen (2017). Spatial and temporal analysis of wind effects on PV modules: Consequences for electrical power evaluation. Solar Energy 147, 292–299.



15:52 - 16:10

Development of a digital twin of the temperature distribution in datacenters

Eric Terry

Actiflow

Aim and Approach

(max 200 words)

The aim of the project was to provide datacenter operators with a non-invasive technology to monitor the real time 3D temperature distribution in the entire datacenter room. The developed solution is called 4DCOOL and uses both

real time temperature measurement data and a 3D CFD (Computational Fluid Dynamics) model. The principle is to define how and where the CFD computer model is uncertain and then use a mathematical optimization technique to nudge the model towards the data within the limits of the uncertainty. With the right approach, the model stays physically correct but is much closer to the sensor data.

Scientific Innovation and Relevance

(max 200 words)

The 3D temperature monitoring tool is based on the fusion of CFD and real time measurement data. There are well established techniques to do the envisaged

fusion which have been common in the field of weather prediction for decades, but far less applied to indoor climate applications.

The energy consumption of large datacenters is high, and the total energy consumption of the entire datacenter market is rising faster than in any other industry. Cooling accounts for 25-40% of datacenter energy consumption. Competition in the market and CO2 reduction requirements are drivers in the market to reduce energy consumption, but this introduces significant risks for datacenter operators. Mainly for colocation datacenters, it is crucial to have a maximum uptime of the datacenter, and to respect at all times the maximum air temperature provided to the customer’s servers as specified in the service level agreement (SLA) with the customer. As a result, the industry is rather conservative to change or optimize cooling in the datacenter room, especially without good monitoring tool. Therefore, it is important to provide datacenter operators with a non-invasive technology to monitor the real time 3D temperature distribution in the entire datacenter room.

Preliminary Results and Conclusions

(max 200 words)

The 4DCOOL monitoring tool was tested through 2 pilot projects in 2 different datacenters in Belgium and the Netherlands. During the pilot projects, one set of sensors was used as input for the software, and a second set of sensors was used to validate the output of the tool. In both pilot projects, the tool provided a reliable image of the temperature distribution in the datacenter.

In both pilot projects, the insights from the developed tool led to a re-arrangement of the lay-out of the perforated tiles and the cooling unit settings, leading to cooling energy cost savings of more than 20%.

The result of our development project is a validated software tool called 4DCOOL that can be coupled to existing DCIM (Data Center Infrastructure Management) software which provides the user with a quasi-real-time image of the temperature distribution in the datacenter room. Furthermore, the software has the functionality to set up “what-if” scenarios for the operator to assess the

consequences of (i) expanding or moving of the heat load, (ii) adjusting the settings of the cooling units or (iii) rearranging the perforated tile configuration in the floor or ceiling.

Main References

(max 200 words)

- Geir Evensen (2003). The Ensemble Kalman Filter: theoretical formulation and practical implementation, Ocean Dynamics (53): 343-367

- Koomey J.G. (2008). Worldwide electricity used in data centers, stacks.iop.org/ERL/3/034008

 
14:40 - 16:10Session W3.2: Ensuring high quality building simulations
Location: Concert Hall - Artiestenfoyer
Session Chair: Steffen Petersen, Aarhus University
Session Chair: Kristof Vlieghe, Viessmann
Concert Hall - Artiestenfoyer 
 
14:40 - 14:58

Characterised sun path patches as a way to design better shading

Andrew Corney1, Vladimir Bajic2

1Trimble SketchUp, United Kingdom; 2Trimble SketchUp, USA

Aim and Approach

(max 200 words)

Interviews and surveys identified that a large proportion of architects use shadow analysis as the primary (and often only) way of designing shading systems.

The aim of this project was to find ways to enhance this natural workflow by providing low friction ways to get a better understanding about sun quality. The aim is to improve shading outcomes by providing better information in established workflows.

The concepts were developed and studied as part of a beta program with 190 participants, mostly archtiects. The beta program started with a range of surveys and interviews asking participants about if and how they design shading systems.

A beta application with the proposed workflow was then developed, firstly as a web-app, and then as a SketchUp extension.

Scientific Innovation and Relevance

(max 200 words)

Understanding sun path diagrams and shadows are incredibly important and included in most architectural design courses.

However in most climates the time of day and time of year, the cloudiness of the sky, intensity of the sun and outside temperature as well as the nature of the building affect whether or not shading is really useful or not. Annual simulations with analysis tools are outside the capabilities of most architects and even where they are available, the use is sporadic because it does not fit neatly in the architect's design workflow.

A key reason identified in our research (over years) is that any friction in the architectural design process drastically reduces the effectiveness of building simulation. The work here sought to provide a defensible and useful improvement to the information used, while minimising the level of friction added to the design process and we feel this is very relevant.

Preliminary Results and Conclusions

(max 200 words)

So far in the beta program research has shown that a very large proportion of participants (mostly architects, all SketchUp users) use the shadow functionality in SketchUp to design shading systems without using any other hourly simulation input.

Although many participants reported not remembering how to use sun path diagrams, most were able to pass straightforward tests on what the information presented is. This meant that the division of the sun path into 3 types of characterised "patches" (overheating, warming or passive) could also be interpreted and applied to inform design.

We used reverse shadow projections for shading strategies onto sun path diagrams to create visual explanations as to the effectiveness of different shading approaches. These could be generated quickly and easily while using SketchUp and provided a way to dynamically see how important and effective shading devices are, without the need to take the model into dedicated simulation.

We hope results from prototypes being made available for design use will also be presentable at the conference.

Main References

(max 200 words)

Interviews and Discussions with architects and specialists participating in our beta program from the United States and Europe.

Sun, Wind and Light: Architectural Design Strategies, M, DeKay, GZ Brown



14:58 - 15:16

Modelling solar shadings with metallic slats for optimal daylighting. What parameters should we focus on?

Bertrand Deroisy1, Marshal Maskarenj2, Sergio Altomonte2

1Belgian Building Research Institute, Brussels, Belgium; 2Université Catholique de Louvain, Louvain-la-Neuve, Belgium

Aim and Approach

(max 200 words)

Designing high performance buildings requires a proper consideration of solar exposures and indoor climate conditions. In the current context of the climate change it must be possible to guarantee adequate thermal and visual comfort even with future climate conditions. Overheating is obviously an increasing risk factor for the occupants, especially in urban settings due to heat island effect. Meanwhile daylight, other than providing suitable conditions for vision, affects our physiological and psychological health. Solar shading systems with tilting metallic slats are commonly used to control daylight provision and energy transfer to the interior space. However, a precise characterization of their performance has to include many parameters, which are not always available. Very often, component level metrics are used to compare solutions, but these are neither consistently related to a specific context nor they are reliable for more complex building envelope assemblies. This study identifies the factors that most relevantly impact on the robustness of performance outcomes of daylighting simulations. It focuses specifically on the scattering properties of metallic surfaces and the shape of the slat profile on simulation results.

Scientific Innovation and Relevance

(max 200 words)

The main solar shading systems used in Europe include roller blinds and venetian blinds, consisting of stacked and guided metallic slats. Standardized methods for characterizing solar-optical properties of regular transparent materials are well established, but robust methods do not exist yet for light scattering, shading and daylighting systems, such as venetian blinds, which have specific angle-dependent properties. Simulations of daylight provision and thermal radiative transfer through complex building envelopes needs to integrate the spatial distribution aspects from the materials and surfaces finishes used in the models. A comparison of standard methods, up-to date building level simulation techniques and advanced optical simulation tools was done in this study. Exact geometrical models of the slats and the possibility to integrate measured BSDF data to describe the scattering properties of the slat surface were used in advanced optical simulations techniques. A detailed analysis of the sensitivity of a set of input parameters (sky model, optical properties, slat design, glazing type) on the global performance of the solar shading systems was done. The results of this study allow to identify the simulation and modelling parameters that should be primarily considered when evaluating the daylighting performance of a building envelope with solar shading systems.

Preliminary Results and Conclusions

(max 200 words)

Out of the four simulation parameters considered, the factor that has the largest effect on the consistency of simulation outcomes is represented by the tilt angle of the slats. An adequate and accurate setting of the tilt angle, based on solar altitudes and internal requirements, is essential to guarantee comfortable conditions for the building occupants at any time. The light scattering properties of the slat surfaces have a non-negligeable impact on daylight provision. Real slats are often relatively specular. Modelling them as diffuse surfaces generally underestimate transmittance ratios when the system is in a relatively open position. The shape of the slats can also have a significant influence when special profiles are used. However the difference between a flat slat and a typical curved slat is not detectable with advanced optical simulation techniques. The current building simulation applications do not allow to accurately estimate the impact of special slat profile shapes on daylighting performance. Large differences were observed between the two simulation based methods for medium sun angles. In general, more precise models are required whenever relatively specular surfaces, or special slat profiles, are used in shading systems.

Main References

(max 200 words)

Capperucci, Loonen R., Hensen J.L.M, Rosemann A.L.P. (2018). Angle-dependent optical properties of advanced fenestration systems - Finding a right balance between model complexity and prediction error. Building simulation 12, 113–127.

Inanici M., Hashemloo A. (2017). An investigation of the daylighting simulation techniques and sky modeling practices for occupant centric evaluations. Building and Environment 113, 220-231.

Konis T., Lee E.S. (2015). Measured daylighting potential of a static optical louver system underreal sun and sky conditions. Building and Environment 92, 347-359.

Kuhn T., (2017). State of the art of advanced solar control devices for buildings. Solar Energy 154, 112-133.

Nilsson A., Jonsson J. (2010). Light-scattering properties of a Venetian blind slat used for daylighting applications. Solar Energy 84, 2103-2111.

Tzempelikos A., Chan Y-C. (2016) Estimating detailed optical properties of window shades from basic available data and modeling implications on daylighting and visual comfort, Energy and Buildings 126, 396-407.

Uribe D., Vera S., Bustamante W., McNeil A., Flamant G. (2019). Impact of different control strategies of perforated curved louvers on the visual comfort and energy consumption of office buildings in different climates, Solar Energy 2019, 495-510.



15:16 - 15:34

A spectral model for longwave radiant heat transfer: influence of new generation polymers in BES

Edouard Walther, Antoine Hubert

AREP L'hypercube, France

Aim and Approach

(max 200 words)

In Building Energy Simulation (BES), the modeling of radiation relies on a dual-band model: longwave, infra-red radiant heat transfer is linearised and computed separately from shortwave, solar radiation. This robust technique originates from the optical properties of glass, the latter being opaque to longwave radiation.

In the recent year, the use of polymer materials such as ETFE or LDPE has become popular in stations, greenhouses or leisure halls (Giuliano et al. 2010). In comparison with glass, they exhibit attractive features such as a reduced weight or higher visible transmittance.

The dual-band model is consistent for standard glass but appears to be unadapted to the aforementioned materials. Indeed, they are partially transparent to longwave radiation, with transmissivities ranging from 20 to 80% depending on the wavelength, which particularly affects the “greenhouse effect”.

The present work aims at creating a spectral model for radiation transfer in multiple bandwidths and evaluating the influence of the new generation polymer materials on the greenhouse effect. Determining the ability of classical BES models for the simulation of radiant heat transfer through polymers depending on their cutoff wavelength in the infra-red domain is also an objective of this work.

Scientific Innovation and Relevance

(max 200 words)

A few references mention applications using ETFE (Cremers & Marx 2016), (Hu et al. 2016), (Cremers & Marx 2017), however, to the best of the authors’ knowledge, the effect of longwave transmissivity on indoor/outdoor radiation seems to be ignored. In the consulted literature, only (Poirazis et al. 2009) point out the lack of information about transmissivity in the longwave domain for polymers like ETFE and highlight the need for an extensive radiative model with experimental validation.

It hence appears interesting to explore the actual influence of such optical properties on heat transfer within buildings, which a spectral model reliably takes into account. Indeed, depending on the value of transmissivity in the infra-red range, this phenomenon may possibly be negligible as suggested in (Poirazis et al. 2009).

Preliminary Results and Conclusions

(max 200 words)

A single-room, “shoebox” house serves as a test case. The window transmittance model follows (Curcija et al. 2018) and the wall model is built after a 4R3C scheme (Fraisse et al. 2002). In order to confirm the accuracy of the building model, a cross-validation is led using the EnergyPlus software with mere glass on transparent the southern walls. The results obtained show that the spectral model compares well with the dual-band model of EnergyPlus.

Preliminary results have demonstrated that ETFE does not filter the infrared radiations as efficiently as glass does, which is beneficial for longwave radiant cooling, however, given the higher transmittance in the solar spectrum, the temperature in buildings with ETFE may exceed the glazed building's temperature.

A comparison of the ETFE with LDPE, which transmissivity is even higher in the longwave range is currently explored. The differences obtained are in favour of a spectral model for BES of buildings with longwave transparent polymers.

Main References

(max 200 words)

Vox, Giuliano & Teitel, M. & Pardossi, Alberto & Minuto, A. & Tinivella, F. & Schettini, Evelia. (2010). Sustainable greenhouse systems. Sustainable Agriculture: Technology, Planning and Management. 1-80.

Poirazis, H., Kragh, M., & Hogg, C. (2009, July). Energy modelling of ETFE membranes in building applications. In 11th International IBPSA Conference, Glasgow, Scotland (Vol. 144).

Curcija, C., Vidanovic, S., Hart, R., Jonsson, J., & Mitchell, R. (2018). WINDOW Technical Documentation. Lawrence Berkeley National Laboratory.

Cremers, J., & Marx, H. (2016). Comparative study of a new IR-absorbing film to improve solar shading and thermal comfort for ETFE structures. Procedia Engineering

Cremers J, Marx H. A new printed and spatially transformed ETFE foil provides shading and improves natural light and thermal comfort for membrane structures'. PLEA 2017.

Poirazis H, Kragh M, Hogg C. Energy modelling of ETFE membranes in building applications. In11th International IBPSA Conference, Glasgow, Scotland 2009

Hu J, Chen W, Qiu Z, Zhao B, Zhou J, Qu Y. Thermal performances of ETFE cushion roof integrated amorphous silicon photovoltaic. Energy Conversion and Management. 2015

Fraisse G, Viardot C, Lafabrie O, Achard G. Development of a simplified and accurate building model based on electrical analogy. Energy and buildings. 2002



15:34 - 15:52

Modelling naturally ventilated double skin facade in Modelica

Alessandro Dama1, Jaime Varas del Ser1, Ettore Zanetti1, Francesco Casella1, Olena Kalyanova Larsen2

1Politecnico di Milano, Italy; 2Aalborg University, Denmark

Aim and Approach

(max 200 words)

In recent decades, Double Skin Facades (DSF) and their thermal performance have been subject of numerous studies in literature. Despite this, the availability of rapid, robust and accurate tools for evaluating the performance of naturally ventilated double skin facades is still very limited, since only few published models have been accompanied by a complete experimental validation under variable boundary conditions, i.e. temperatures, solar irradiance and wind. Furthermore, the integration and/or coupling of such models within building energy simulation tools remains a complex task due to the multiple functionalities of the transparent and ventilated façade interacting with the building environment.

To this purpose this paper presents the implementation and validation of a model for naturally ventilated DSF in Modelica. The aim is to provide an open and robust tool easily integrable in the recent development of Modelica building libraries. Modelica, in fact, is an object oriented and open source programming language that has gained attention in the last decade, thanks to its ability to standardize and simplify modelling and thanks to its high potential when working with multi-domain systems.

Scientific Innovation and Relevance

(max 200 words)

An ongoing international cooperation, under IBPSA Project 1, aim at creating a freely accessible, editable, documented and validated Modelica simulation library to support the design and operation of buildings and districts [1]. This work would contribute to the building library developments.

Validations of the selected model for naturally ventilated DSF was already presented in [2] and [3]. The further advantage of its implementation in Modelica is, thanks to its modularity, the possibility to perform again the model validation under different choices of the boundary conditions, isolating different model domains. Moreover, in this study the validation was extended to the simulation of a building module with the south facing DSF, giving a proof o the integration of the DSF model with the zone thermal model in Modelica. The experimental database used was provided by a field study on a full scale DSF "The Cube" carried out in Aalborg, Denmark [4].

Finally, a sensitivity analysis was performed on the convection in the ventilated channel, on the glazing solar absorptions and on the thermal capacities. It gave insight on the most relevant choices for the model parameters.

Preliminary Results and Conclusions

(max 200 words)

Preliminary results of the DSF model implementation in Modelica had confirmed its capability to predict the variability of the mass flow rate, mainly due to the variable wind conditions, and improved its accuracy in predicting the outlet temperature and the inward heat flux. Such improvements are likely due to a better coupling in Modelica of the thermal and fluid-dynamic problems. The sensitivity analysis shows the importance of an accurate and detailed optical characterization of the window system and the role of the correlation adopted for the convection inside the ventilated channel. Otherwise, thermal capacity of glazing does not influence significantly the prediction even using a simulation timestep of fifteen minutes.

Main References

(max 200 words)

[1] https://ibpsa.github.io/project1/

[2] A. Dama, D. Angeli, O. K. Larsen, Naturally ventilated double-skin facade in modeling and experiments, Energy and Buildings 144 (2017) 17–29

[3] A. Dama, M. Dopudi, O. K. Larsen, Experimental Validation of a Model for Naturally Ventilated Double-Skin Facades in proceedings of 7th International Building Physic Conference, IBPC 2018, Syracuse, NY, USA

[4] O. Kalyanova, Empirical Validation of Building Simulation Software: Modelling of Double Facades Final Report Technical Report IEA ECBCS Annex43/SHC Task 34 Validation of Building Energy Simulation Tools Subtask E



15:52 - 16:10

Open-source photovoltaic model for early building planning processes: Modeling, application and validation

Laura Maier1, Michael Kratz1,2, Christian Vering1, Philipp Mehrfeld1, Dirk Müller1

1RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, Aachen, Germany; 2currently studying at ETH, Zurich, Switzerland

Aim and Approach

(max 200 words)

Within buildings, a great potential to reduce CO2 emissions exists. One common solution is to integrate renewable energy sources (RES) into BESs which are called interconnected systems. In this regard, PV systems are a promising technology as they enable sector coupling on the one hand and support local electricity generation on the other hand.

In order to exploit the full potential of PV systems, they have to be systematically integrated into the local control system. In this context, the proper sizing of PV modules plays an important role. This decision is made at an early planning stage. However, the optimum sizing of PV systems is challenging due to dynamic boundary conditions such as weather and its interdependencies with the whole BES, i.e. mounting’s influence. In this context, simulation models facilitate the process of estimating future operation of PV modules.

We contribute to a more simplified planning process by applying the following steps:

1. We develop an open-source Modelica PV model for wafer-based cells, which is based on manufacturer data only and is suitable for early stage design.

2. We validate the model with measured data to prove mounting’s influence.

Scientific Innovation and Relevance

(max 200 words)

None of the researched Modelica PV models cover all of the following aspects:

• Open-source access

• Parameters based on manufacturer data only

• Integration of the mounting´s influence

• Validation based on measurement data

In addition, we quantify the influence of ohmic losses on the DC power output.

Preliminary Results and Conclusions

(max 200 words)

In order to evaluate the model accuracy, we compare the simulated electrical energy of selected days with the measured one. The simulation mostly overestimates the electricity generation. This is caused by effects such as ageing, ohmic losses (OL) or staining, which are neglected within the model. Apart from that, the highest relative error is observed for the roof system at around 16 %.

To understand higher model errors for some days, we analyze the DC power output of the roof system in more detail. Here, we compare the simulated and the measured power on the day with the highest model error. The absolute difference between the data sets increases with raising power output. When also taking into account the OL, the model error is decreased to 7 %. Here, we estimate the OL using the simulated cell temperature and measured current.

For a simulative OLs estimation, the detailed interconnection of the implemented PV modules has to be known. This information is not necessarily given at an early planning stage and complicates the parameterization tremendously. As this contradicts the model’s aim to be simple and used at an early stage of planning, OLs are neglected.

Main References

(max 200 words)

Batzelis, E., Papathanassiou, S.. A Method for the Analytical Extraction of the Single-Diode PV Model Parameters (2016). IEEE Transactions on Sustainable Energy 7, 504-512.

Boyd, M. (2015). High-Speed Monitoring of Multiple Grid-Connected Photovoltaic Array Configurations.

Boyd, M. (2017). Performance Data from the NIST Photovoltaic Arrays and Weather Station. Journal of Research of the NIST 122.

Duffie, J.A., Beckman, W.A. (edited by). (2013). Solar engineering of thermal processes. Fourth edition. Wiley. Hoboken, NJ (USA).

King, D.L., Boyson, W.E., Kratochvill, J.A. (edited by). (2005). SANDIA REPORT SAND 2004-3535 Unlimited Release Printed December 2004 Photovoltaic Array Performance Model.” (2005).

Müller, D., Lauster, M., Constantin, A., Fuchs, M., Remmen, P. (2016) AIXLIB- An open-source Modelica library within the IEA-EBC Annex 60 Framework. Proceedings from BauSIM2016. Dresden (Germany), 14-16 September.

 
14:40 - 16:10Session W3.3: Buildings paving the way for the energy transition
Location: Concert Hall - Studio 1
Session Chair: Dariusz Heim, Lodz University of Technology
Session Chair: Sorin Comsa, Daikin
Concert Hall - Studio 1 
 
14:40 - 14:58

The influence of uncertainties in grid electricity primary energy conversion factors on multi-criteria trade-off solutions in façade design optimisation

Samuel Bruno de Vries, Roel C.G.M. Loonen, Jan L.M. Hensen

Eindhoven University of Technology, Netherlands, The

Aim and Approach

(max 200 words)

Decision-making in façade design requires balancing of various competing performance aspects, including visual comfort, daylighting performance, thermal comfort, investment and operation costs, and CO2 emissions. These decisions are influenced by assumptions about cost parameters, HVAC specifications, and carbon intensity of grid electricity and other fuels.

The goal of this paper is to investigate how the optimal trade-off solutions and corresponding performance of façade design (glazing and advanced solar shading) change as a result of variations in the technical and economic context.

These topics are investigated through a case-study focussing on a novel sun tracking vertical blind which can switch between solar reflecting and solar absorbing states. The performance of this system is assessed in relation to other conventional solutions for controlling the admission of solar heat gains and daylight.

A multi-scale and multi-domain simulation approach is used to evaluate performance in terms of daylight glare probability simplified, spatial daylight autonomy, primary energy consumption and total costs. The influence of possible changes in the technical and economic context are considered by testing the influence of different assumptions regarding, cost parameters, the efficiency of heating and cooling systems and the primary energy ratio (PER) of electricity on energy performance and total costs.

Scientific Innovation and Relevance

(max 200 words)

The increasing share of renewables in the electricity mix will decrease the overall carbon emissions of electricity in relation to other fuels and cause larger temporal fluctuation in the emissions of grid electricity. The emissions associated with building electricity demand will therefore become increasingly time-of-use dependant and building energy performance predictions are therefore clouded by uncertainties regarding the future electricity mix. Addressing these uncertainties in the facade design process is a topic that is still largely unexplored.

In modern high-performance office buildings, interactions between glazing, automated solar shading controls, daylight dimmable lighting and occupants are defining for building energy performance. The façade design problem therefore requires a multi-physics approach and is interwoven with control optimisation.

This paper utilizes a novel simulation tool chain, that:

- Employs a multi-physics co-simulation approach that allows for multi-objective decision support in the selection of solutions for controlling the admission daylight and solar energy.

- Uses a multi-scale simulation approach to evaluate the effects of a complex multi-state shading system on whole building performance.

- Enables co-optimisation of solar shading control and façade design aspects.

- Allows for evaluating design alternatives in combination with different HVAC systems and electricity mix scenarios, and robust solutions to be identified.

Preliminary Results and Conclusions

(max 200 words)

- This study identifies façade design and solar shading control solutions that offer beneficial trade-offs in visual comfort, daylighting, energy performance and building related costs. In particular, it uncovers high-performing solutions that are robust to uncertainties regarding costs, the future electricity mix and the efficiency of HVAC systems.

- The advanced vertical blind control strategy offers superior daylighting, visual comfort and energy performance compared to conventional solutions. This conclusion is robust to different assumptions regarding PER scenarios, HVAC concepts and glazing systems.

- The presence of a daylight dimming system is an essential condition for the sun-tracking vertical blind system to offer improvements in energy performance over conventional automated control approaches.

- More efficient cooling systems and improvements in the PER of electricity will decrease the relative importance of energy performance in relation to other performance aspects in the selection of glazing and solar shading systems.

- If daylight dimming systems and efficient cooling systems become ubiquitous, and more renewable electricity from PV gives rise to a favourable PER in the summer months, reducing solar heat gains will become less important in the selection of glazing and the control of solar shading systems. Effective daylighting becomes the most defining aspect in improving energy performance.

Main References

(max 200 words)

Aslihan, Tavil, and S. Lee Eleanor. 2006. "Effects of Overhangs on the Performance of Electrochromic Windows." Architectural Science Review.

Atzeri, Anna Maria, Andrea Gasparella, Francesca Cappelletti, and Athanasios Tzempelikos. 2018. "Comfort and energy performance analysis of different glazing systems coupled with three shading control strategies." Science and Technology for the Built Environment 24 (5):545-58.

Cubi, Eduard, Ganesh Doluweera, and Joule Bergerson. 2015. "Incorporation of electricity GHG emissions intensity variability into building environmental assessment." Applied energy 159:62-9

Méndez Echenagucia, Tomás, Alfonso Capozzoli, Ylenia Cascone, and Mario Sassone. 2015. "The early design stage of a building envelope: Multi-objective search through heating, cooling and lighting energy performance analysis." Applied energy 154:577-91.

Pilechiha, Peiman, Mohammadjavad Mahdavinejad, Farzad Pour Rahimian, Phillippa Carnemolla, and Saleh Seyedzadeh. 2020. "Multi-objective optimisation framework for designing office windows: quality of view, daylight and energy efficiency." Applied energy

Shen, Eric, Jia Hu, and Maulin Patel. 2014. "Energy and visual comfort analysis of lighting and daylight control strategies." Building and Environment 78:155-70.

St-Jacques, Max, Scott Bucking, and William O'Brien. 2020. "Spatially and temporally sensitive consumption-based emission factors from mixed-use electrical grids for building electrical use." Energy and Buildings 224:110249.



14:58 - 15:16

Analysis of HVAC retrofit layouts including solar cooling system with adsorption heat pump - Modelling, dynamic simulation and multi-criteria evaluation

Paola Colombo, Giulia Filippini, Rossano Scoccia, Marcello Aprile, Mario Motta

Department of energy, Politecnico di Milano, Italy

Aim and Approach

(max 200 words)

Within the perspective of increasing attention to the environmental issues and energy policies, the construction sector has a crucial role. Buildings are responsible of the 40% of the total energy consumptions and generate the 36% of greenhouse gases in European Union. In addition, the long lifecycle of buildings leads to a very small rate of replacement of the existing stock. Thus it is necessary to pursue the objective of building retrofitting, starting from the older buildings stock, which has the largest energy saving potential. The European R&D project Heat4Cool addresses the specific construction segment of residential buildings, proposing innovative, efficient and cost-effective solutions for the space heating and cooling retrofitting. Among the Heat4Cool pilot sites, this work deals with the HVAC systems retrofitting for a residential building located in Valencia (Spain). From the energy analysis of the pre-retrofit status, this paper summarizes the steps of definition, modelling and evaluation of renovation layouts of the heating and cooling system, with the goal to identify the optimal configuration in terms of energy consumption reduction and costs.

Scientific Innovation and Relevance

(max 200 words)

For the specific pilot site under analysis, renovation layouts of the heating and cooling system, including solar thermally driven adsorption heat pumps, are defined, modelled and evaluated. In TRNSYS 17 environment, the renovation layouts are modelled and tested, with the aim to evaluate the impact of the use of different technologies in terms of energy consumptions, costs and environmental impact. Parametric simulations are performed for the implementation of solar assisted thermal driven adsorption chiller, exploiting its potentiality for the solar cooling. The optimal case, among the ones simulated, analysed and compared, is determined through a multi-criteria decision analysis that takes into account energetic, environmental, economic and financial parameters.

Preliminary Results and Conclusions

(max 200 words)

The solar thermal system resulted able to cover till the 52% of the heating (SH+DHW) energy needs, while the use of solar assisted adsorption chiller showed its potentialities in the reduction of the energy consumptions for the cooling needs, providing a contribution on the total cooling energy production that reaches the 27%. All the simulation resulted in line with the PE reduction target (with values up to 67%), while the discounted payback periods are around 10 years under certain reference conditions.

Main References

(max 200 words)

I. Daßler, W. Mittelbach, Solar cooling with adsorption chillers, in: Energy Procedia, Elsevier Ltd, 2012: pp. 921–929. https://doi.org/10.1016/j.egypro.2012.11.104.

H.T. Chua, K.C. Ng, A. Malek, T. Kashiwagi, A. Akisawa, B.B. Saha, Modeling the performance of two-bed, silica gel-water adsorption chillers, Int. J. Refrig. 22 (1999) 194–204. https://doi.org/10.1016/S0140-7007(98)00063-2.

M. Schicktanz, T. Núñez, Modelling of an adsorption chiller for dynamic system simulation, Int. J. Refrig. 32 (2009) 588–595. https://doi.org/10.1016/j.ijrefrig.2009.02.011.

V. Palomba, S. Vasta, A. Freni, Q. Pan, R. Wang, X. Zhai, Increasing the share of renewables through adsorption solar cooling: A validated case study, Renew. Energy. 110 (2017) 126–140. https://doi.org/10.1016/j.renene.2016.12.016.

Solar Energy Laboratory, TRNSYS - TRaNsient SYstem Simulation program.

E. Zanetti, R. Scoccia, S. Garone, M. Aprile, M. Motta, L. Mazzarella, Energy Saving Potentials of a Centralized Hybrid Heating System via Adaptive Model Predictive Control in a Northern Italy Residential Building, Proc. Build. Simul. 2019 16th Conf. IBPSA. 16 (2020) 2925–2932. https://doi.org/10.26868/25222708.2019.210631.

R. Scoccia, T. Toppi, M. Aprile, M. Motta, Absorption and compression heat pump systems for space heating and DHW in European buildings: Energy, environmental and economic analysis, J. Build. Eng. 16 (2018) 94–105. https://doi.org/10.1016/J.JOBE.2017.12.006.



15:16 - 15:34

Performance comparison of static and adjustable photovoltaic panels

Dawid Wolosiuk, Matthias Schuss, Ardeshir Mahdavi

Vienna University of Technology, Austria

Aim and Approach

(max 200 words)

Building-integrated photo-voltaic (PV) panels can increase the fraction of renewable sources in the energy mix. Roof installations of PV panels are thus encouraged in many countries [1]. Thereby, one of the relevant questions concerns the cost-benefit analysis of static (fixed) installations versus dynamic installations capable of solar tracking. Moreover, in addition to entirely static option and the solar tracking options, it is conceivable to conduct regular directional adjustments "manually". Whereas this latter option would be more expensive than conventional static installations (due to the needed mechanical gear and manual labour), it would require significantly fewer resources that the solar tracking variants. The present contribution applies a high-resolution modelling approach and cost-estimation routines to compare the energetic output and estimated installation and maintenance cost of static, fully dynamic, and multiple instances of recurrent manually executed directional adjustment of the PV panels.

Scientific Innovation and Relevance

(max 200 words)

The energetic efficiency of PV systems can be enhanced via the selection of the optimal orientation of the panels. In many instances, this orientation is determined based on the calculation of energy again over typically longer periods of time (e.g., over a typical year). Regular adjustment of the orientation (e.g., via automated solar tracking) can further increase the magnitude of the solar energy harnessed. However, this comes with notable increase of the cost of installing and maintaining the panels. In certain instances, regular manually-based adjustments may offer an alternative that is both energetically attractive and feasible form the point of view of installation and operation costs. However, related decisions require information about the energetic benefits and installation and maintenance costs of adjustable solutions. Likewise, in order to conduct a reliable cost-benefit analysis, the added value of higher adjustment frequency must be weighed against the expenses associated with higher frequencies.

Preliminary Results and Conclusions

(max 200 words)

A computational platform has been developed involving a generator for high-resolution sky models, algorithms for the dynamic calculation of incident solar radiation [2]. Thereby, different panel slopes and directions can be parametrically assessed. The platform is coupled with an existing application that computes, for different types of PV panels, the magnitude of generated electricity as a function of the incident solar radiation [3, 4]. The comparison of static and adjustable systems is performed for three different climatic regions and different energy management scenarios, involving autarkic and grid-connected buildings with and without local storage capacity.

Main References

(max 200 words)

[1] A. Jäger-Waldau, "PV Status Report 2019". EUR 29938 EN, Publications Office of the European Union, Luxembourg, 2019.

[2] D. Wolosiuk and A. Mahdavi, "Application of ontologically structured data for building performance analysis". Proceedings of the 11th annual Symposium on Simulation for Architecture & Urban Design (SimAUD), 2020, pp. 297-302.

[3] J. S. Stein, W. F. Holmgren, J. Forbess and C. W. Hansen, "PVLIB: Open source photovoltaic performance modeling functions for Matlab and Python". 2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC), Portland, OR, 2016, pp. 3425-3430

[4] W. F. Holmgren, C. W. Hansen, and M. A. Mikofski. "pvlib python: a python package for modelling solar energy systems". Journal of Open Source Software, 3(29), 884, 2018.



15:34 - 15:52

The path towards a zero fossil fuel Building

Frederik Maertens, Wim Boydens

boydens engineering, Belgium

Aim and Approach

(max 200 words)

A competition has been launched to build a +/-80.000m² mixed-use building in Belgium. The client requirements were high; class A comfort, BREEAM daylight compliance, low energy consumption, light building structure, maintenance friendly and, above all, a flexible and functional building.

As a starting point, the idea of the architect was to create the new building with minimal impact on the existing infrastructure and neighbouring surroundings.

Next to that main idea, the cladding material should be resistant to flash rust (coming from the rails) and easy to maintain.

A curtain wall façade was the obvious starting point of the design. Simulations were used to optimize the amount and location of the glazed elements, enhancing thermal and visual comfort while keeping the glazing as cladding material.

Scientific Innovation and Relevance

(max 200 words)

• The presentation of this case gives insight in the use of simulations for specific multidisciplinary design choices in designs of large buildings.

• The case illustrates how dynamic simulations can assist and add value to multidisciplinary integrated designs.

• The presentation shows a practical step by step methodology to optimize the façade with various combined simulation tools.

Preliminary Results and Conclusions

(max 200 words)

The developed façade made it possible to reach a building demand of 13kWh/m² for heating and 6kWh/m² for cooling, a passive building definition; including the renovated building part. As end result of this combination of simulations a visually fully glazed façade (seen from the outside) but insulated and provided with internal solar shading could still result in optimal indoor comfort in a passive way .

Main References

(max 200 words)

no reference studies used



15:52 - 16:10

Retrofit of a 1970’s apartment building into energy plus, results of a prototype apartment

Eelke P. Bontekoe1, Wilfried G.J.H.M. van Sark1, Liza Looijen2, Paul Das3, Joris van den Heiligenberg3, Arno F. Peekel4

1Utrecht University, The Netherlands; 2Hogeschool Utrecht, The Netherlands; 3Bos Installatiewerken, The Netherlands; 4Utrecht Sustainability Institute (USI), The Netherlands

Aim and Approach

(max 200 words)

To reduce the CO2 emissions of the building stock in the Netherlands, 1.5 million existing houses have to be turned into NZEB (Near Zero Energy Buildings) before the end of 2030 [1]. This paper describes a case study in which we investigate if this challenge can be taken a step further by retrofitting a 10 story apartment building from the 1970’s in such a way that it becomes a positive energy building.

Scientific Innovation and Relevance

(max 200 words)

A new building design is made, where the thermal envelope is insulated, and facades are being upgraded by means of new modular building elements. These elements perform very well on insulation, contain systems for low temperature heating, have integrated window blinds and building-integrated photovoltaic (BIPV) modules. Central heat pumps on the roof of the building provide heat for space heating and domestic hot water (DHW). Each apartment has a booster heat pump to boost the DHW temperature above 60 degrees Celsius. More than 1100 PV modules are placed on the roof as well as on the facades of the building. To accommodate a part of these modules a special steel framing is designed on top of the building .

The energy requirements of the retrofitted building design were calculated with the help of the NZEB tool, which is based on PHPP v9 [2]. The energy production of the PV system is modeled by means of the PVSites software tool [3]. To understand if the proposed concept works in real life, a pilot apartment has been realized where the energy demand and the comfort levels have been monitored for about 1 year.

Preliminary Results and Conclusions

(max 200 words)

The results of monitoring temperature, CO2 and relative humidity in the apartment, proved that in general the comfort is well within the limits of the latest European standards [4]. Only during an exceptional heatwave, overheating was measured. Over the course of the year, the heat pumps for space heating and DHW required more energy than expected. This was mainly due to a malfunctioning space heater. In case this heater would function properly, the PVSites tool showed that the energy production for the whole building is larger than the energy demand.

We can conclude that with our prototype apartment we have proven that it is possible to retrofit an apartment building such that it produces more energy by its PV system than its energy demand. Lessons learnt from the pilot project are already implemented in the next step of the project, where the whole building is being retrofitted.

Main References

(max 200 words)

[1] Ministerie van Economische zaken en Klimaat, “Klimaatakkoord,” Klimaatakkoord, p. 250, 2019.

[2] Passive House Institute, “Passive House Planning Package v9 (PHPP9).” 2019.

[3] PVSites, “Homepage of PVSites software package,” 2019. [Online]. Available: https://www.pvsites.eu. [Accessed: 17-May-2019].

[4] Council of the European Union, “EN 16798-1:2019 Indoor environmental input parameters for design and assessment of energy performance of buildings- addressing indoor air quality, thermal environment, lighting and acoustics,” 2019..

 
14:40 - 16:10Session W3.4: Historical and heritage buildings
Location: Concert Hall - Studio 2
Session Chair: Staf Roels, KU Leuven
Session Chair: Wouter Van de Walle, Daidalos Peutz
Concert Hall - Studio 2 
 
14:40 - 14:58

Estimation of the thermal properties using modal identification method and optimal experiment design applied to historical building walls

Benjamin Kadoch1, Julien Berger2

1Aix Marseille Université, CNRS, IUSTI UMR 7343, 13453, Marseille, France; 2Laboratoire des Sciences de l’Ingénieur pour l’Environnement (LaSIE), UMR 7356 CNRS, La Rochelle Université, CNRS, 17000, La Rochelle, France

Aim and Approach

(max 200 words)

Thermal properties of the walls require to be known precisely since they play a crucial role on the assessment of the building energy efficiency [1, 2]. The unknown properties can be estimated by solving parameter estimation problem [3]. This procedure aims at minimizing a cost function between the model numerical predictions and the experimental observations. Nevertheless, retrieving the unknown parameters needs a large number of computations of the heat transfer problem. To decrease this computational effort, model reduction techniques can be employed. Several methods are reported in the literature to model the physical phenomena in building walls [4]. The Modal Identification Method (MIM) can be a pertinent choice since it has been demonstrated successful applications for inverse problem [5]. A complementary technique is the optimal experiment design methodology [6, 7] which determine the length of the measurement observations. The optimal design is searched according to the conditions of the experiment. Carrying the measurement for the optimal experiment design ensure to estimate the unknown parameter with the highest accuracy. The aim of this paper is to propose a fast and accurate parameter estimation method. This methodology is then used to estimate the thermal diffusivity of historical buildings.

Scientific Innovation and Relevance

(max 200 words)

An innovative methodology is proposed based on two concepts. First, a reduced order model based on MIM method is used to significantly reduce the computational time of the direct problem without loosing accuracy. The reduced model is based on a state space representation where the matrices are built during a learning step. The latter is based on a minimization procedure between the predictions of the reduced and complete models. An interesting point is that the model is built to compute the field of interest and its sensitivity to the unknown parameter. The sensitivity is known straightforwardly using the matrices of the reduced model. The second concept is the optimal experiment design methodology. It is employed to determine a reduced sequence of observations. Three advantages are enhanced with this approach. First, it reduces the inherent computational cost of a posteriori model reduction methods since the learning step is carried for a reduced sequence. Then, the chosen sequence is optimal to estimate the parameter with accuracy. In addition, the inverse problem is solved only for a few days of observations. It reduced again the computational effort to retrieve the parameter.

Preliminary Results and Conclusions

(max 200 words)

A first case study is proposed to validate the MIM model reduction method. This MIM model is built with a signal based on 4 values of thermal diffusivity. Then, the MIM model shows a very satisfying accuracy and efficiency to simulate the direct problem over a wide range of diffusivity. Regardless the inherent cost of the learning step, the model cut by 5 the computational cost of the direct problem. The model is also evaluated in the framework of inverse problem with simulated experimental observations. The unknown parameter is estimated with an error lower than the measurement uncertainty. After this validation case, the whole methodology is applied to more realistic ones. The issue is to estimate the thermal diffusivities of several old building walls. These are monitored during four months with three sensors drilled inside. Results for one wall give that the estimated diffusivity, using a model of order 10, is three times higher than the one provided by standards. Moreover, the parameter is estimated with an algorithm 5 times faster. These preliminary results show that the methodology is efficient to calibrate the model with a reduced computational effort and give an accurate thermal diffusivity.

Main References

(max 200 words)

[1] A. Jumabekova, J. Berger, and A. Foucquier. Sensitivity analysis in the framework of parameter estimation problem for building energy performance: a continuous derivative based approach. submitted, 2019.

[2] T. Busser, M. Pailha, A. Piot, and M. Woloszyn. Simultaneous hygrothermal performance assessment of an air volume and surrounding highly hygroscopic walls. Building and Environment, 148:677 – 688, 2019.

[3] J. Berger, H.R.B. Orlande, N. Mendes, and S. Guernouti. Bayesian inference for estimating thermal properties of a historic building wall. Building and Environment, 106(SupplementC):327–339, 2016.

[4] J. Berger, N. Mendes, S. Guernouti, M. Woloszyn, and F. Chinesta. Review of Reduced Order Models for Heat and Moisture Transfer in Building Physics with Emphasis in PGD Approaches. Archives of Computational Methods in Engineering, pages 1–13, 2016.

[5] M. Girault, D. Petit, and E. Videcoq. The Use of Model Reduction and Function Decomposition for Identifying Boundary Conditions of A Linear Thermal System. Inverse Problems in Engineering, 11(5):425–455, 2003.

[6] D. Ucinski. Optimal Measurement Methods for Distributed Parameter System Identification. CRC Press, New York, 2004.

[7] J. V. Beck and K. J. Arnold. Parameter Estimation in Engineering and Science. John Wiley and Sons, New York, 1977.



14:58 - 15:16

Living lab ‘De Schipjes’: a zero-fossil-fuel energy concept in the historic city center of Bruges

Jelger Jansen1,2, Frederik Maertens3, Wim Boydens3,4, Lieve Helsen1,2

1KU Leuven, Department of Mechanical Engineering, Celestijnenlaan 300 box 2421, 3001 Leuven, Belgium; 2EnergyVille, Thor Park 8320, 3600 Genk, Belgium; 3boydens engineering, Kooidam 6, 8200 Bruges, Belgium; 4Ghent University, Department of Architecture and Urban planning, Jozef Plateaustraat 22, 9000 Ghent, Belgium

Aim and Approach

(max 200 words)

This contribution aims to show the role and importance of dynamic simulations in the research project of 'De Schipjes', a social housing neighborhood located in the historic city center of Bruges. Firstly, an introduction is given in which some background information is provided on Almshouses 'De Schipjes' and in which the importance of dynamic simulations in the project is clarified, being to design and operate a 100% renewable energy sources-based district heating network. Secondly, the methodology and results (in the form of figures and tables) of both simulation studies are briefly discussed in two different sections. Finally, a conclusion is drawn.

Scientific Innovation and Relevance

(max 200 words)

This contribution illustrates the importance of dynamic building simulations to design a 100% renewables-based district heating network in an historic city center and to optimize the control strategy during design and commissioning. Furthermore, this contribution shows the feasibility of such a zero-fossil-fuel energy concept in a historic city center. This is relevant for other historic centers in Europe (and beyond), where this concept might be reproduced or serve as an inspiration.

Preliminary Results and Conclusions

(max 200 words)

The contribution focuses on two different stages in the project of 'De Schipjes'. In a first stage of the project, building simulations allowed an extensive comparison of four energy system scenarios (e.g. by using performance indicators) which led to the design of a low-temperature fully renewable energy sources-based district heating network supplied by a ground source heat pump and solar thermal collectors. In a later stage, detailed simulations were performed to assess different rule-based control (RBC) algorithms impacting the energy performance of the energy system and thermal comfort. In this contribution, four promising adapted RBCs are mentioned and the simulation results of these RBCs in comparison with a reference RBC are provided.

Main References

(max 200 words)

Aertgeerts, A. (2016). IWT Proeftuin De Schipjes: Theoretische benadering van het verbeteringspotentieel. Internal Report, KU Leuven, Belgium, 2016.

Boydens, W., Feyaerts, S., Vandermeulen, A., Helsen, L., Jansen, J. (2020). Control strategy assessment of a small GSHP sourced DH system with end user DHW booster heat pumps. 12th IEA Heat Pump Conference. Jeju (Korea), 11-14 May 2020 (Postponed to April 26-29, due to outbreak of Coronavirus). Accepted for oral presentation.

Feyaerts, S. (2019). Impact van de regeling op de performantie van een klein thermisch net voor godshuizen, De Schipjes, te Brugge. Master’s thesis, KU Leuven, Belgium, 2019.

Jorissen, F., Reynders, G., Baetens, R., Picard, D., Saelens, D., Helsen, L. (2018). Implementation and verification of the IDEAS building energy simulation

library. Journal of Building Performance Simulation 11(6), 669-688.

Van Kenhove, E., Aertgeerts, A., Laverge, J., Janssens, A. (2015). Energy Efficient Renovation of Heritage Residential Buildings Using Modelica Simulations. 14th Conference of International Building Performance Simulation Association. Hyderabad (India), 7-9 December 2015.

Wetter, M., Zuo, W., Nouidui, T.S., Pang, X. (2014). Modelica Buildings library. Journal of Building Performance Simulation 7(4), 253-270.



15:16 - 15:34

Simulation-based Optimization of thermal Comfort in a heritage Manor House

Torsten Schwan, Rene Unger

EA Systems Dresden GmbH, Germany

Aim and Approach

(max 200 words)

The preservation of historical building structures, especially in urban areas, is a particular challenge for cities, municipalities and private investors due to the changing requirements of space usage and energy supply. The primary goal is to find the best possible compromise between the future usability of the building as well as the preservation and conservation of the historical building fabric. A novel approach is the integration of a closed inner shell in timber construction within the existing structures. On the one hand, this enables the complete conversion of the building with regard to the latest space utilization and design requirements. On the other hand, this allows the compliance with the latest energy standards to be implemented with minimal intervention in the historical building envelope.

However, this noble goal places enormous challenges on architects and engineers and requires adequate evaluation tools for finding an optimal, individual solution. This paper describes an approach for the use of a hybrid digital twin model [1] based on Modelica building models and high-resolution energy system measurement data to evaluate the existing situation and various optimization measures for indoor air comfort and energy efficiency in a heritage-protected urban cottage.

Scientific Innovation and Relevance

(max 200 words)

This paper actually addresses two types of innovation in the construction sector. On the one hand, the way in which a historic building is to be adapted to existing space and energy standards. On the other hand, the paper shows a new approach in the building sector of using a hybrid digital twin model to analyze, evaluate and optimize various measures in an early stage of the renovation.

The hybrid approach in the creation of the digital twin model combines the use of high-resolution, electronic measurement technology in the building with the development of dynamic simulation models of the building and its energy supply [2]. The combination of both methods provides a maximum of model accuracy by calibrating the model with temporally high-resolution measurement data and thus offers the engineers a platform for finding and digitally testing valid optimization measures in the real building. Particularly with regard to the individuality of historical buildings, a methodology is thus shown that can be used in a variety of practical applications.

Preliminary Results and Conclusions

(max 200 words)

The work steps shown here began shortly after the owner put the presented historical building into operation. For this reason, high-resolution measurement data of energy consumption and thermal room behavior from several weeks and various supply situations were already available at the start of the project.

The modelling and calibration of the models enabled the mapping of the individual building behavior with an error tolerance of less than 3%.

The cause of the original shortfall in thermal energy could be determined with the help of the models and three different optimization measures were tested and evaluated. The developed solution enabled a reduction of the energy demand by up to 57% while at the same time significantly improving thermal comfort in more than 99% of the year.

Main References

(max 200 words)

[1] Chinesta, F.; Cueto, E.; Abisset-Chavenne, E.; Duval, J.; Khaldi, Fouad (2018). Virtual, Dig-ital and Hybrid Twins: A New Paradigm in Data-Based Engineering and Engineered Data. Archives of Computational Methods in Engineering.

[2] Schwan, T., Schmitt S.; Castellani, A. (2019). Calibration of HVAC system models with monitoring data – Digital Twin meets measurement data. ESI Forum in Germany, Berlin, Germany.



15:34 - 15:52

A hybrid measurement-simulation approach to determine the reflectance map of a historic tapestry

John Mardaljevic1, Eleonora Brembilla2, Stephen Cannon-Brookes3, Nigel Blades4

1Loughborough University, United Kingdom; 2TU Delft, Netherlands; 3UCL, United Kingdom; 4National Trust, United Kingdom

Aim and Approach

(max 200 words)

In historic buildings, curators and conservators are increasingly choosing to display rooms under daylight illumination conditions comparable to how those spaces were originally used.[1] All predominantly daylit spaces will experience considerable spatio-temporal variation in natural illumination. However, monitoring of light levels to control exposure is only carried out at a limited number of locations, perhaps just one per space/room.[2] Light-sensitive objects such as large tapestries therefore present particular challenges since the daylight dose across the tapestry could vary significantly from that recorded at the periphery of the tapestry. An earlier study in a historic setting employed high dynamic range imaging (HDRI) to measure cumulative daylight exposure by using numerous wallpaper patches as proxy illuminance targets.[3] Knowing the reflectance of the wallpaper, the incident illuminance at each target patch could be derived from the patch luminance recorded in the HDR image (taken every 10 minutes). It was then possible to reconstruct the prevailing daylight illuminance incident on the paintings hung on the walls by interpolation across the wallpaper patches using a Kriging algorithm. The new approach uses the tapestry itself as the target. This required a novel hybrid HDR measurement – lighting simulation approach.

Scientific Innovation and Relevance

(max 200 words)

The setting for the study is the Volury Room at Ham House, Richmond-upon-Thames (UK). The Volury contains a set of three large seventeenth century tapestries that occupy most of the three (non window) walls. The technique to derive incident illuminance from camera measured HDR luminance requires knowledge of the diffuse reflectance of the target. For scenarios such as the Volury, it was necessary to devise a method to determine the per-pixel reflectance (or albedo map) for the entire tapestry in situ without disturbing it. The basis for this was controlled illumination of the tapestry by a LED studio lamp. Characterisation of the lamp photometry allows determination of the illumination field across the tapestry. However, the room-reflected component added significantly to the light incident on the tapestry. A novel hybrid multi-step approach using HDR capture combined with Radiance lighting simulation was devised to account for the room-reflected component of illumination from the lamp.[4] With the HDR camera fixed in place for long-term monitoring, HDR captures were made of the tapestries illuminated by the LED panels. The new approach opens up the possibility of camera-based measurement of daylight dose in historic showrooms.

Preliminary Results and Conclusions

(max 200 words)

The LED lamp photometry (measured under controlled conditions) was imported into a Radiance simulation of the Volury based on an accurate 3D model of the room. The simulated illumination field from the LED incident on one tapestry was predicted for increasing number of ambient bounces to account for the room reflected component until convergence was achieved. The Radiance simulated illumination field was then applied to the camera captured HDR image of the tapestry (illuminated by the LED lamp) via a warping procedure. The warping was required to precisely align the simulated illumination field with the camera HDR image. Next, using the precisely-aligned illumination field, the albedo map for the tapestry was derived from the HDR image. This was repeated for the other large tapestry visible from the camera position. At corresponding points across the simulated illumination fields there was remarkable agreement (<10%) with in situ point measurements of illuminance across the two tapestries taken at the time of HDR capture (under LED illumination). The derived albedo maps for the two tapestries are presented. Thereafter, the albedo maps will be used to derive the cumulative long-term (several months) daylight illumination across the two tapestries from the (automated) HDR capture images.

Main References

(max 200 words)

[1] National Trust. The National Trust Manual of Housekeeping. Anova Books, London, 2011.

[2] N. Blades, K. Lithgow, S. Cannon-Brookes, and J. Mardaljevic. New tools for managing daylight exposure of works of art: case study of Hambletonian, Mount Stewart, Northern Ireland. Journal of the Institute of Conservation, 40(1):15–33, 01 2017.

[3] J. Mardaljevic, S. Cannon-Brookes, N. Blades, and K. Lithgow. Reconstruction of cumulative daylight illumination fields from HDR: Theory, deployment and in-situ validation. Lighting Research & Technology, (accepted), 2020.

[4] G. Ward Larson, R. Shakespeare, J. Mardaljevic, C. Ehrlich, E. Phillips, and P. Apian- Bennewitz. Rendering with Radiance: The Art and Science of Lighting Visualization. San Francisco: Morgan Kaufmann, 1998.

 
14:40 - 16:10Session W3.5: Improving indoor environmental quality
Location: Concert Hall - Kamermuziekzaal
Session Chair: Natalia Giraldo Vasquez, Federal University of Santa Catarina
Session Chair: Jean-Baptiste BOUVENOT, INSA Strasbourg/ICube Laboratory
Concert Hall - Kamermuziekzaal 
 
14:40 - 14:58

The impact of light distribution and furniture layout on meeting light exposure objectives in an office - a simulation case study

Megan Danell1, Steffen Hartmeyer1, Lisa Petterson2, Robert Davis3, Marilyne Andersen1, Siobhan Rockcastle4

1Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland; 2SRG Partnership, Portland, OR United States of America; 3Pacific Northwest National Lab, Portland, OR, United States of America; 4University of Oregon, Eugene, OR United States of America

Aim and Approach

(max 200 words)

While the building industry is beginning to embrace the impact of light on non-visual responses that drive human health, there are limited design guidelines for how to implement effective light distribution and achieve recommended circadian light exposure. Human-centric factors that impact eye-level light exposure in a private office include the seating location, view direction, and eye level of an occupant, which interact with the light distribution, intensity, and spectrum of any given light source. This study presents a simulation-based study that compares various light distribution patterns, furniture configurations, and seating/standing positions to illustrate the impacts on human health potential from a non-visual health perspective.

The space used in our case study is an existing architectural office located in Portland, OR. Multiple luminaires and light distribution patterns are compared under different furniture layouts. The ALFA (Adaptive Lighting for Alertness) plug-in for Rhino is used to simulate Equivalent Melanopic Lux (EML) values for a series of hourly and daily time steps [4]. Electric light sources are simulated using industry-standard IES files and results are compared for both seated and standing view positions.

Scientific Innovation and Relevance

(max 200 words)

A number of simulation techniques have emerged in recent years as a means to predict how varying factors within a space affect non-visual light exposure for building occupants. These techniques include the simulation of vertical illuminance values in incremental measurements across one or more view directions [3, 4, 6]. Recent work has also compared the impact of daylight [1, 3, 4, 5] and electric lighting sources [4, 5, 6, 7] on the health of indoor occupants. A recent study compared the impact of various overhead light sources on vertical eye-level exposure and horizontal task-plane illuminance [2]. This paper builds upon these studies by comparing a broader range of occupant-centric and spatial conditions that can impact the lighting design of an office space.

The novelty of our research lies in the comparison of light distribution patterns, furniture layout, and ergonomics within a private office space. Because eye-level light exposure accounts for light reflected off of vertical surfaces, luminaires that distribute light onto vertical surfaces and are located closer to the eye are potential assets for improving healthy lighting conditions. This work has the potential to bridge research with practical lighting design recommendations to improve the health and well-being of occupants located in private offices.

Preliminary Results and Conclusions

(max 200 words)

Our results reveal a variety of intriguing outcomes. Intuitively, the combination of electric light and daylight sources systematically outperforms scenarios that rely exclusively on electric light only. While 36 out of 48 simulated scenarios achieved the minimum threshold for the WELL Building Standard of 150 melanopic lux (assuming continuous exposure between 9am and 1pm), less than half achieved the recommended 250 melanopic lux, despite achieving recommended task-plane illuminance values.

Comparing results from the various light distribution scenarios (direct vs. direct/indirect ceiling-mounted luminaires and wall-wash luminaires), the fixtures that provided a significant wall wash component achieved the highest EML values. This indicates the potential for vertical light distribution to act as a source of healthy light exposure that has not yet been thoroughly studied. A comparison of various ergonomic positions also reveals the variability in EML exposure between standing and seated positions. Further development of this proposal would contribute to the currently limited design guidelines for implementing effective lighting design to achieve circadian light exposure through the use of furniture configurations, eye level, and lighting distributions.

Main References

(max 200 words)

[1] Acosta, I., Leslie, R., & Figueiro, M. (2017). Analysis of circadian stimulus allowed by daylighting in hospital rooms. Lighting Research & Technology, 49(1), 49–61.

[2] Jarboe, C., Snyder, J., & Figueiro, M. (2020). The effectiveness of light-emitting diode lighting for providing circadian stimulus in office spaces while minimizing energy use. Lighting Research & Technology, 52(2), 167–188.

[3] Amundadottir, M., Rockcastle, S., Sarey Khanie, M., & Andersen, M. (2017). A human-centric approach to assess daylight in buildings for non-visual health potential, visual interest and gaze behavior. Building and Environment, 113, 5–21.

[4] Saiedlue, S., Amirazar, A., Hu, J., & Place, W. (2019). Assessing Circadian Stimulus Potential of Lighting Systems in Office Buildings by Simulations. ARCC Conference Repository.

[5] Danell, M., Amundaddottir, M. L., & Rockcastle, S. (2020). Evaluating Temporal and Spatial Light Exposure Profiles for Typical Building Occupants. SimAUD Conference Proceedings.

[6] Dai, Q., Huang, Y., Hao, L., Lin, Y., & Chen, K. (2018). Spatial and spectral illumination design for energy-efficient circadian lighting. Building and Environment, 146, 216–225.

[7] Rockcastle, S., Danell M., Petterson, L., & Amundadottir, M. (2020). The Impact of Behavior on Healhty Circadian Light Exposure Under Daylight and Electric Lighting Simulations. ACEEE Conference Proceedings.



14:58 - 15:16

Evaluating the use of photobiology-driven alertness and health measures for circadian lighting design

Athina Ji-Hae Alight, J. Alstan Jakubiec

University of Toronto, John H. Daniels Faculty of Architecture, Landscape, and Design, Toronto, Canada

Aim and Approach

(max 200 words)

The aim of this project is to evaluate a novel daylighting and electric lighting design workflow that assesses a space based upon light’s impact on human photobiology-driven alertness, and health. The method, being published in a separate submission to the conference, works by translating timeseries spectrally-resolved light simulation data into photobiologically driven measures mediated by the response of intrinsically-photosensitive retinal ganglion cells (ipRGCs) in the human eye. These measures are used as input to a dynamic photobiological framework that accounts for light history, timing, spectrum, and homeostatic body rhythms. These measures are then visualised in a novel manner to communicate the impacts of lighting on space occupants. To demonstrate the value of this process, the predicted non-visual biological effects of six design variables (artificial lighting schedules, artificial light spectrum, occupant location, window spectral transmittance, surface reflectance, and two space designs) are simulated. The design variables are also applied to the frameworks suggested by Mardaljevic et al. (2013), Amundadottir et al. (2017), the WELL standard (2018), and Konis (2019) to test how these models respond to variations in spectrum and light exposure and how they differ in the resulting evaluation of architectural design.

Scientific Innovation and Relevance

(max 200 words)

Several frameworks have been developed to evaluate lighting design for non-visual biological effects, which this paper compares and evaluates. Unlike light for visual tasks, the non-visual/circadian system, is sensitive to the timing of light exposure. The circadian system is also responsive to shorter wavelengths than the visual system. Illuminance that is appropriate to perform visual tasks therefore may not be enough to entrain circadian rhythms or maintain alertness and performance. Insufficient light after waking or excess light before sleep onset disrupts circadian rhythms with harmful health consequences. Furthermore, circadian disruption is cumulative, and depends on circadian entrainment in the recent past. As a result of these complexities, our model takes the history, timing, intensity, and spectrum of light exposure into account. To the best of our knowledge, the workflow presented in this paper is the only one that predicts explicit biological effects of light and spectrum over time rather than circadian light potential. Through implementing our model, we will demonstrate the results of the model and how architectural design can directly impact an occupant’s circadian health. Our comparative analysis will showcase how predicting alertness and health measures differs from previous work and impacts the evaluation of architecture.

Preliminary Results and Conclusions

(max 200 words)

For the six design parameters and using our new model, the following alertness and health photobiological measures are calculated: subjective alertness measured by the Karolina Sleepiness Scale, mean reaction time, attention lapses, and performance at rote tasks, the amount of circadian phase shift per day, the time of peak melatonin concentration, and the percent of total melatonin suppression per day due to acute light exposure.

The comparative analysis with previous models is based on two aspects: (1) comparisons of quantitative lighting units and (2) assessing differences in design evaluation outcomes as positive or negative. A compilation of the circadian calculation and evaluation methods used in existing photobiological lighting design evaluative frameworks (Mardaljevic et al. 2013, Amundadottir 2017, WELL Standard 2018, Konis 2019) are compared in this manner.. Each framework’s responsiveness to lighting types (daylight, electric, or hybrid), evaluation timeframe (instantaneous, daily, or annual), and lighting design interventions is also compared and discussed.

Main References

(max 200 words)

Amundadottir, M. L., Rockcastle, S., Khanie, M. S., & Andersen, M. (2017). A human-centric approach to assess daylight in buildings for non-visual health potential, visual interest and gaze behavior. Building and Environment, 113, 5-21.

Circadian lighting design. (2018). https://standard.wellcertified.com/light/circadian-lighting-design.

International WELL Building Institute, WELL Building Standard Circadian Lighting Design Feature. https://standard.wellcertified.com/light/circadian-lighting-design Last accessed 6/3/2020.

Konis, K. (2019). A circadian design assist tool to evaluate daylight access in buildings for human biological lighting needs. Solar Energy, 191, 449-458.

Mardaljevic, J., Andersen, M., Roy, N., & Christoffersen, J. (2013). A framework for predicting the non-visual effects of daylight–Part II: The simulation model. Lighting Research & Technology, 46(4), 388-406.

Solemma.com. ALFA. https://solemma.com/Alfa.html.

Tekieh, T., Lockey, S. W., Robinson, P. A., McCloskey, S., Zobaer, M. S., & Postnova, S. (2020). Modelling melanopsin-mediated effects of light on circadian phase, melatonin suppression and subjective sleepiness.



15:16 - 15:34

Integrated analysis of daylight and solar access building requirements and performance in urban environments in Estonia

Francesco De Luca, Abel Sepúlveda

Tallinn University of Technology, Tallinn, Estonia

Aim and Approach

(max 200 words)

Daylight and solar access are essential aspects of the indoor environmental quality of buildings. Adequate quantity of daylight helps to perform tasks with ease and its distribution increases architectural quality [1]. Appropriate direct solar access helps the entrainment of the circadian rhythm and the improvement of physiological and psychological well-being of occupants [2]. Thus, in most countries, regulations prescribe minimum quantities of daylight and direct solar access [3, 4].

The new EU standard Daylight in Buildings [5], to be acquired in Estonia, for daylight requires a minimum Daylight Factor (DF) of 0.7% on 95% of the simulation plane and of 2.2% on 50% of the plane closer the window. For solar access in dwellings it requires a minimum of 1.5 hours of exposure to sunlight calculated during one day between February 1st and March 21st.

The present study investigates optimal dwelling room parameters for 1) the fulfillment of both DF and sunlight requirements of the new EU standard in urban environments, where sunlight provision is most critical, and 2) adequate daylight availability. The aim is to help local authorities in the acquisition of the new EU standard and to provide designers with guidelines for the fulfillment of both requirements.

Scientific Innovation and Relevance

(max 200 words)

The new EU standard requires different daylight but same sunlight quantity for the different countries. There are no studies about the relation between the two requirements in Estonia. Additionally, recent studies proved the scarce reliability of the Daylight Factor metric in predicting daylight availability in the country [6,7].

The innovation of the study lies in the integrated analysis of building performance for daylight and solar access at northern latitudes in urban environments. Additionally, it contributes to the assessment of the reliability of the DF requirements through climate based daylight simulations using the metrics of the LM-83-12 method Spatial Daylight Autonomy (sDA) and Annual Sunlight Exposure (ASE) [8]. The first predicts reliably daylight availability, the latter potential visual discomfort.

The integrated analysis of DF and solar access, DF and sDA, ASE and solar access permits to assess the efficacy of the requirements of the new EU standard for Estonia and to develop guidelines for the design in urban environments.

For the study a parametric model is realized that generate variations of a sidelit room orientation, window size, shading (upper floor balcony) and surrounding environment. The parametric model automates the calculation of solar access and the different daylight simulations at each variation.

Preliminary Results and Conclusions

(max 200 words)

Simulations for 144 room variations, 8 orientations, 9 window sizes and 2 shading states are performed for March 21st without surrounding buildings and in three urban environments in Tallinn.

Without surrounding buildings, DF, that doesn’t depend on orientation, is fulfilled by 66.7% of 18 variations, solar access, sDA and ASE by 62.5%, 49.3% and 56.9% of 144 variations respectively. DF and sunlight together, and sDA and ASE together, as required by the EU standard and by the LM-83-12 method, are fulfilled by 27.8% and 13.9% of all variations respectively.

In the three urban environments, DF is simulated also for the 8 orientations due to the different external obstructions. On average, solar access, DF, sDA and ASE are fulfilled by 51.8%, 20.3%, 17.8% and 68.5%, DF and sunlight, and sDA and ASE together are fulfilled by 14.4% and 3.7% of all variations respectively.

Preliminary results show the different fulfillment of DF and sunlight, the influence of the urban environment and the difficulty to achieve the two pair of performance together, and the daylight overestimation by the DF requirement in Estonia. The paper will present detailed simulation results and parameters necessary to fulfil the different metrics singularly and in pairs as required.

Main References

(max 200 words)

1 - Reinhart, C.F. 2014. Daylighting Handbook I. Fundamentals. Designing with the Sun. Building Technology Press, Cambridge (USA).

2 – Lockley, S.W. 2009. Circadian rhythms: influence of light in humans. In: Squire LR (ed), Encyclopedia of Neuroscience (Vol. 2), Cambridge, MA, USA: Academic Press, 971–988.

3 – Dogan, T. and Park, Y.C. 2019. A critical review of daylighting metrics for residential architecture and a new metric for cold and temperate climates. Lighting Research & Technology, 51, 206–230.

4 – Darula, S., Christoffersen, J. and Malikova, M. 2015. Sunlight and insolation of building interiors. Energy Procedia, 78, 1245–1250.

5 - European Commission 2018. EN 17037:2018 Daylight in Buildings.

6 - De Luca, F., Kiil, M., Simson, R., Kurnitski, J. and Murula, R. 2019. Evaluating daylight factor standard through climate based daylight simulations and overheating regulations in Estonia. Proceedings of 16th IBPSA International Conference and Exhibition (BS2019), 3968-3975.

7 – Sepúlveda, A., De Luca, F., Thalfeldt, M. and Kurnitski, J. 2020. Analyzing the fulfillment of daylight and overheating requirements in residential and office buildings in Estonia. Building and Environment, 180, 107036.

8 - Illuminating Engineering Society 2013. IES LM-83-12 Approved Method: IES Spatial Daylight Autonomy (sDA) and Annual Sunlight Exposure (ASE).



15:34 - 15:52

Machine learning techniques for the daylight and electric lighting performance predictions

Chantal Basurto, Oliver Paul, Jérôme H. Kämpf

Idiap Research Institute, 1920 Martigny, Switzerland

Aim and Approach

(max 200 words)

Despite the technological advance in the field of energy efficient buildings, the achievement of adequate lighting interior environments it is still a tight corner spot. The latter, due to the complex interplay occurring at different levels of the building performance, involving energy related and occupant’s comfort issues. Such as, achieving a right balance between an increased daylight penetration for the reduction of heating and lighting loads in winter, while minimizing the risk of glare for the occupants. Providing an adequate solar protection while achieving a sufficient daylight provision at task area is a similar quest for summer time. Therefore, in order to undertake the intrinsically linked energy efficiency and occupant’s comfort goals, recent research endeavors involve an integrated assessment of daylight, electric lighting, blinds and lighting controls. Nowadays, such evaluations are mostly performed with the use of computer simulations, which, due to the complexity of the issue, are still highly demanding in terms of computing time and performance capabilities; besides of the human-hours invested on the interaction with distinctive tools and interfaces. In order to improve the response time of daylight and electric lighting performance-predictions, machine learning techniques based on existing daylighting evaluation methods, are employed using surrogate models.

Scientific Innovation and Relevance

(max 200 words)

In order to achieve an optimal control of blinds and electric lighting, a predictor model is employed to evaluate the impact of a blind’s position choice on the work-plane illuminance and of glare in the occupant’s eye. Including the predictor model in a Model Predictive Control (MPC) is the ultimate goal, aiming to obtain a quasi-real-time optimization of the building parameters, to provide visual comfort to the user with less electric lighting. Ubiquity is the main feature of this work, since the predictor model is derived from year-round simulations generated by the RADIANCE based matrix multiplication methods, where all possible blinds positions and weather conditions are considered. Simulation cost is another relevant feature of this work, since, due to the longer time that RADIANCE simulations require to complete, the predictor model is rather based on a statistical surrogate model realized with an Artificial Neural Network (ANN). A database is first produced and employed for the training of the surrogate model. Its input parameters are the weather data (direct and diffuse irradiance), sun and blinds position and electric lighting intensity, while the output data are key performance indicators (average work-plane illuminance and DGP glare index), for specific users.

Preliminary Results and Conclusions

(max 200 words)

The method is applied to an office building located in Martigny, Switzerland, where two specific rooms are modeled and used as a case-study to demonstrate the model’s predictor capabilities. The two models were created using Sketchup, while their material properties (reflectance, transmittance and other physical parameters) were measured using a Minolta Chromameter (CR-200b) and Gloss-meter (GM-060). The models were then calibrated according to on-site illuminance measurements obtained during the summer 2020, where the accuracy was reported as below 20%, providing the target precision for our surrogate model. A nearby weather station is used to gather direct and diffuse irradiance on hourly basis for the whole year under study. The vast amount of data obtained from the year-round RADIANCE simulations was determinant for defining the function between the inputs and outputs. Different ANNs (FFN, LSTM, GRU and CNN) are tested and compared to provide satisfactory precision for both illuminance and DGP, at a negligible simulation cost due to the data obtained beforehand from the RADIANCE simulations. The electric lighting contributions to the illuminance on the work-plane are computed separately, and the potential glare from the luminaires neglected. The developed surrogate model is finally validated against actual RADIANCE simulations and real monitoring.

Main References

(max 200 words)

Ayoub, M., 2020. A review on machine learning algorithms to predict daylighting inside buildings. Solar Energy 202, 249–275. https://doi.org/10.1016/j.solener.2020.03.104

McNeil, A., 2013. The Five-Phase Method for Simulating Complex Fenestration with Radiance (Tutorial). Lawrence Berkeley National Laboratory, Berkeley, CA.

McNeil, A., 2012. A validation of the RADIANCE Three-Phase Simulation Method for Modeling Annual Daylight Performance of Optically Complex Fenestration Systems. Journal of Building Performance Simulation 1–14.

McNeil, A., 2010. The three-phase method for simulating Complex Fenestration with Radiance. Lawrence Berkeley National Laboratory, Berkeley, CA.

Nault, E., Moonen, P., Rey, E., Andersen, M., n.d. Predictive models for assessing the passive solar and daylight potential of neighborhood designs: A comparative proof-of-concept study. Building and Environment 116, 1–16. http://dx-doi.org/10.1016/j.buildenv.2017.01.018

Ward, G., 1985. RADIANCE lighting simulation software.

Wienold, J., Christoffersen, J., 2005. Towards a new daylight glare rating. Presented at the LUX Europa: Lighting for Humans, Berlin, Germany.

Zhaoyang, L., Cheng, S., Qi, D., 2020. A daylight-linked shading strategy for automated blinds based on model-based control and Radial Basis Function (RBF) optimization. Building and Environment 177. https://doi.org/10.1016/j.buildenv.2020.106854



15:52 - 16:10

Luminance distributions in consultancy: Simulations or measurements?

Thijs Willem Kruisselbrink

Peutz BV, Netherlands, The

Aim and Approach

(max 200 words)

The luminance distribution is suitable tool to assess the lit environment in a holisitic manner. The luminance distribution is either simulated or measured. Both approaches have different strenghts and weaknesses. This work presents an analysis of the strenghts and weaknesses of the two approaches in order to find the most suitable approach for specific cases in consultancy.

Scientific Innovation and Relevance

(max 200 words)

The lit environment is an intangible, but rather relevant component of the built environment, impacting performance, comfort, health and well-being. Research has shown that the lit environment has a multidimensional character. Consequently, the lit environment cannot be fully grasped by singular metrics that are often utilized inconsultancy such as the daylight factor (DF). Preferably, multiple metrics, associated to e.g. amount,distribution or directionality of light, are utilized todescribe the lit environment. However, despite significant effort, the research community has not found asatisfactory and holistic metric to capture the lit environment as a whole.

Alternatively, the luminance distribution can be a suitable means to describe the lit environment, as it contains information on the majority of relevant metrics. Nevertheless, practical implementation of the luminance distribution, simulation or measurement, in consultancy is rather limited. In addition to the advantagesof the luminance distribution, multiple limitations areassociated to its use, both for simulations and mea-surements.

Preliminary Results and Conclusions

(max 200 words)

Simulations or measurements of the luminance distributions are suitable for different consultancy cases. Simulations are more suitable to find a optimal solution for the lit environment while measurements are able to assess a problem associated to the lit environment.

Main References

(max 200 words)

Inanici, M. (2006, 6). Evaluation of high dynamicrange photography as a luminance data acquisitionsystem.Lighting Research and Technology 38(2),123–134.

Kruisselbrink, T. (2020, 10).Practical and continu-ous luminance distribution measurements for light-ing quality. Ph. D. thesis, Eindhoven University ofTechnology, Eindhoven.

Kruisselbrink, T., R. Dangol, and A. Rosemann(2018, 6).Photometric measurements of light-ing quality: An overview.Building and Environ-ment 138, 42–52.

Ochoa, C. E., M. B. Aries, and J. L. Hensen (2012, 7).State of the art in lighting simulation for buildingscience: a literature review.Journal of BuildingPerformance Simulation 5(4), 209–233.

Pierson, C., M. Bodart, J. Wienold, and A. Ja-cobs (2017). Luminance maps from High DynamicRange imaging : calibrations and adjustments forvisual comfort assessment. InLux Europa, Ljubl-jana, Slovenia, pp. 147–151.

Reinhard, E., G. Ward, S. Pattanaik, and P. Debevec(2006, 8).High Dynamic Range Imaging: Ac-quisition, Display, and Image-Based Lighting (TheMorgan Kaufmann Series in Computer Graphics).San Fransisco: Morgan Kaufmann Publishers Inc.

Reinhart, C. and O. Walkenhorst (2001). Valida-tion of dynamic RADIANCE-based daylight simu-lations for a test office with external blinds.Energyand Buildings 33(7), 683–697.

Van Den Wymelenberg, K. (2012).Evaluating Hu-man Visual Preference and Performance in an Of-fice Environment Using Luminance-based Metrics.Ph. D. thesis, University of Washington.

 
14:40 - 16:10Session W3.7 (Online Track): Ensuring high quality building simulations
Location: Virtual Meeting Room 1
Session Chair: Dru Crawley, Bentley Systems
Virtual Meeting Room 1 
 
14:40 - 14:58

Design and test of reduced grey-box models adapted to office buildings

Thibault Péan, Soledad Ibañez Iralde, Jordi Pascual, Jaume Salom

IREC Catalonia Institute for Energy Research, Spain

Aim and Approach

(max 200 words)

Simplified models (oftentimes called black and grey box models), allows for high precise results of the energetic behaviour of buildings, with a lower resources demand than more extensive white-box models. Given their potential, a large amount of research has been produced in recent years to develop such simplified models, with the end purpose of performing quick energy demand calculation, or for integration in predictive control schemes. In this line, offices and tertiary buildings represent a large and interesting area of application for such models, given that they have a much higher energy intensity than residential buildings, they tend to be refurbished more often and monitored more closely. The present work aims at developing and adapting simplified models to the specificities of office buildings, to obtain reliable energy calculations and predictions. Such models, provided that they are thoroughly validated and tested, can be used for fast energy demand calculations, integration into overall building management system (that most office buildings already have), predictive controls, or fault detection algorithm for predictive maintenance.

Scientific Innovation and Relevance

(max 200 words)

A large part of the existing literature focuses on simplified models for residential buildings. Office buildings possess some distinct characteristics, which must be taken into account when designing a simplified model. The internal gains from equipment, people and solar irradiation take larger values for this building typology, therefore the cooling demand is usually more important than in residential buildings. This is particularly relevant in the Mediterranean area, where the cooling demand might then represent the critical demand, while in the same region the heating demand is more critical for residential buildings. Furthermore, offices always have mechanical ventilation, which is not the case of most houses in Southern Europe. Finally, the occupancy schedule is more steady and less stochastic, dictated by opening office hours, with an exact opposite occupancy compared to a standard dwelling (i.e. occupants are usually at work when they are not at home), and larger non-occupancy periods (weekends).

To take into account these specificities, a grey-box model was developed, taking as starting point the resistance capacitance (RC) model described in ISO 13790, and modified with more detailed infiltration and ventilation gains. The resulting model has a R4C2 structure.

Preliminary Results and Conclusions

(max 200 words)

To test the proposed grey-box model, a study case of an office building situated in the Mediterranean area of Spain was chosen. A white-box model was first developed with knowledge of the construction elements, and adjusted with monitoring data from the real building in the heating and cooling seasons. The purpose of this intermediate white-box model is to be able to generate different datasets for the identification of the grey-box model. The white-box model was calibrated by adjusting the infiltration rate, the thermal capacity, and the shading coefficient of the windows, leading to a root mean square error of 0.8°C (normalized: 3.5%) between model and data.

The white-box model was used to generate different datasets, exciting the building with a pseudo-random binary signal on the space heating or cooling power. Using these datasets, the identification process aimed at finding the appropriate values of the thermal capacities of the two nodes of the model, and the transmission coefficients of the opaque and transparent construction elements. Using two different optimization process, the best values for these parameters were obtained, leading to a fit of 75% between white-box and grey-box model data, which is satisfactory given the simplicity of the chosen RC model.

Main References

(max 200 words)

ISO. ISO 13790: Energy Performance of buildings - Calculation of energy use for space heating and cooling. (2008).

De Coninck, R., & Helsen, L. (2016). Practical implementation and evaluation of model predictive control for an office building in Brussels. Energy and Buildings, 111, 290–298. https://doi.org/10.1016/j.enbuild.2015.11.014

Reynders, G., Diriken, J., & Saelens, D. (2014). Quality of grey-box models and identified parameters as function of the accuracy of input and observation signals. Energy and Buildings, 82, 263–274. https://doi.org/10.1016/j.enbuild.2014.07.025

De Coninck, R., Magnusson, F., Åkesson, J., & Helsen, L. (2015). Toolbox for development and validation of grey-box building models for forecasting and control. Journal of Building Performance Simulation, (July), 1–16. https://doi.org/10.1080/19401493.2015.1046933

Bacher, P., & Madsen, H. (2011). Identifying suitable models for the heat dynamics of buildings. Energy and Buildings, 43(7), 1511–1522. https://doi.org/10.1016/j.enbuild.2011.02.005



14:58 - 15:16

Evaluation of existing infiltration models used in building energy simulation

Yeonjin Bae1, Jaewan Joe2, Seungjae Lee1, Piljae Im1, Lisa C. Ng3

1Oak Ridge National Laboratory, United States; 2Inha University, South Korea; 3National Institute of Standards and Technology, United States

Aim and Approach

(max 200 words)

This study aims to evaluate the existing infiltration models in EnergyPlus by comparing their simulation results with the infiltration rate estimated from heavily monitored field measurements. A series of tracer gas decay and fan pressurization tests were performed in a full-scale, multizone, and unoccupied commercial building. Three infiltration models within EnergyPlus, one with various sets of coefficients, are used to simulate infiltration rates. The fan pressurization test results were converted to the design infiltration rate for use in each infiltration model. The simulation results were compared with the infiltration rate estimated from the field measurements.

Scientific Innovation and Relevance

(max 200 words)

Infiltration is one of the major sources of uncertainty in building energy simulation. Although many infiltration models exist, their structures and assumptions vary, and often, they are inaccurate for commercial buildings as they were developed based on empirical datasets from residential building models. In this study, tracer gas decay and whole-building pressurization tests were performed in the test building, and the results were used in three different infiltration models available in EnergyPlus. Also, a simulation study was conducted with an empirically validated EnergyPlus model to investigate how the selection of the infiltration model influences the predicted building heating energy consumption.

Preliminary Results and Conclusions

(max 200 words)

In this study, the measured and predicted infiltration rates were compared. The predicted infiltration rates were calculated based on six infiltration models (i.e., three infiltration models from EnergyPlus with various sets of coefficients). Out of six models, “DOE-2”, “EffectiveLeakageArea,” and “FlowCoefficient” based models show significantly large discrepancies withe the measurements. For example, the median value of the predicted infiltration rates using the “DOE-2” model was only15.4 % of the median value of the measured rates. However, the absolute predictive error in the infiltration rate was small because the building is relatively airtight. If the airtightness of the target building is low (i.e., leaky), then the absolute predictive error would also increase.

Also, the simulation results (compared with the infiltration rate estimated from the field measurements) showed that the predicted infiltration rate and the estimated heating energy consumption can be significantly affected by the infiltration model selection.

Main References

(max 200 words)

ASHRAE. 2017. ASHRAE Handbook Fundamentals, American Society of Heating, Refrigerating, and Air-Conditioning Engineers.

ASTM International. 2017. ASTM International Standard E741-11. Standard Test Method for Determining Air Change in a Single Zone by Means of a Tracer Gas Dilution. West Conshohocken, PA: ASTM International.

ASTM. International. 2019. ASTM Standard E779. Standard Test Method for Determining Air Leakage Rate by Fan Pressurization. West Conshohocken, PA.

Emmerich S.J., McDowell T.P. and FAIA W.A. 2007. Simulation of the Impact of Commercial Building Envelope Airtightness on Building Energy Utilization/DISCUSSION. ASHRAE Transactions, 113, p.379.

Gowri K., Winiarski, D., and Jarnagin R. 2009. Infiltration modeling guidelines for commercial building energy analysis (No. PNNL-18898). Pacific Northwest National Lab (PNNL), Richland, WA.

Han G., Srebric J., and Enache-Pommer E. 2015. Different modeling strategies of infiltration rates for an office building to improve accuracy of building energy simulations. Energy and Buildings, 86: 288–95.

Im P., Joe J., Bae Y., New J. R. 2020. Empirical validation of building energy modeling for multi-zones commercial buildings in cooling season. Applied Energy, 261, 114374.

Younes C., Shdid C. A., and Bitsuamlak G. 2012. Air infiltration through building envelopes: A review. Journal of Building Physics, 35(3): 267–302.



15:16 - 15:34

Exploring the possibility of calibrating a whole-building model from the short-term monitoring of selected reference rooms

Ilaria Pittana1, Riccardo Albertin2, Alessandro Prada3, Francesca Cappelletti4, Andrea Gasparella2

1Dep. of Industrial Engineering, University of Padua, Italy; 2Faculty of Science and Technology, Free University of Bozen-Bolzano, Italy; 3Dep. of Civil, Environmental and Mechanical Engineering, University of Trento, Italy; 4Dep. of Architecture and Arts Iuav University of Venice, Italy

Aim and Approach

(max 200 words)

Accurate simulation models of existing buildings provide a reliable picture of building and system behaviour, useful for diagnostic purposes, for designing retrofit interventions or improving the control strategies. Reliable building models can be obtained through monitoring and calibration, aiming at minimizing the discrepancy between predicted and actual performance by fine-tuning the values of the simulation parameters. Analytical calibration methods may become a complex and time expensive process, especially when a large numbers of parameters has to be estimated as in the case of the largest buildings. In addition, overfitting issues can undermine the reliability of the calibration process.

This work explores the possibility of carrying out a model calibration through low-cost and short-term measurements without falling into overfitting issues. In particular, the proposed approach is based on the selection of representative spaces in the buildings, and the identification of multiple monitoring periods during which only a subset of simulation parameters needs to be calibrated. The model is extended to the entire building in a multi-stage and multi-level approach.

The described approach is applied to a Primary School building located in the town of Schio (northern Italy).

Scientific Innovation and Relevance

(max 200 words)

This method has two main advantages that represent its main innovation:

- It uses the measurements inside a small portion of a building (i.e. 9 rooms) to calibrate the whole building, lowering the monitoring costs.

- It uses four short monitoring periods to calibrate different sets of inputs separately, reducing the number of parameters to be optimized each time, thus improving the calibration process.

The described approach is applied to a Primary School building located in the town of Schio (northern Italy). The air temperature and relative humidity in two reference rooms and in the 7 boundary rooms have been monitored, considering four periods, with and without occupancy and during the heating season or the free-floating season. The calibration is developed with a multi-stage approach that considers the four selected periods to calibrate the inputs for which the sensitivity of the air temperature is highest and with a multi-level methodology that extends the parameters calibrated for the two rooms to the entire building and perform a second calibration to estimate the missing parameters.

Preliminary Results and Conclusions

(max 200 words)

Two classrooms have been calibrated during four subsequently periods (Period 1: non-occupied building, passive mode; Period 2: non-occupied building, heating sys¬tem on; Period 3: occupied, passive mode; Period 4: occupied, heating on). The calibrated inputs of the partial-model of the school have been extended to the model of the whole school building in order to build the whole-building initial model in the same periods and to calibrate the residual unknown inputs.

The comparison of the temperature profiles obtained in the different stages and in the different levels of the calibration process with the measured data available in 9 rooms are presented by means of some statistical indices (RMSDavrg, CV(RMSD)avrg and R2avrg). Finally, the measured energy consumption for heating is compared to the calculated one.

Main References

(max 200 words)

ASHRAE. Guideline 14–2002, Measurement of Energy and Demand Savings. American Society of Heating, Ventilating, and Air Conditioning Engineers, Atlanta, Georgia; 2002.

Moriasi D. N., Arnold D. N., Van Liew M. W., Bingner R. L., Harmel R. D., Veith T. L. (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations, Transactions of the ASABE, Vol. 50(3).

Penna P., Cappelletti F., Gasparella A., Tahmasebi F., Mahdavi A., (2015). “Multi-stage calibration of the simulation model of a school building through short-term monitoring.” Special Issue ECPPM 2014 - 10th European Conference on Product and Process Modelling”.

Penna P., Prada A., Cappelletti F., Gasparella A., (2015). “Multi-objective optimization of Energy Efficiency Measures in existing buildings.” Journal of information technology in construction, 20, 132-145. Yang Z., Becerik-Gerber B. (2015). A model calibration framework for simultaneous multilevel building energy simulation. Applied Energy 149 (2015).

Tahmasebi F., Zach R., Schuß M., Mahdavi A. (2012). “Simulation Model Calibration: An Optimization-Based Approach“. Fourth German Austrian IBPSA Conference Berlin University of the Arts.

Tahmasebi F., Mahdavi A. (2013). “A Two-Staged Simulation Model Calibration Approach To Virtual Sensors For Building Performance Data.“ Proceedings of BS2013: 13th Conference of International Building Performance Simulation Association, Chambéry, France, August 26-28.



15:34 - 15:52

A novel multi-domain model for thermal comfort which includes building indoor CO2 concentrations

Sarah Crosby1, Adam Rysanek2

1Department of Mechanical Engineering, University of British Columbia, Vancouver, Canada; 2School of Architecture and Landscape Architecture, University of British Columbia, Vancouver, Canada

Aim and Approach

(max 200 words)

In a prior work, we applied Bayesian logistic regression to correlate and characterize the relationship between perceived thermal comfort, thermal indoor conditions, and non-thermal metrics of indoor environmental quality (IEQ) such as CO2 concentrations and indoor noise levels. That work made use of the COPE dataset, a field study from the early 2000s conducted by the National Research Council of Canada. The study collected objective and subjective IEQ measurements from approximately 800 occupants of open-plan offices in large Canadian and US cities. This work updates the findings of the prior study by adding over 100 new samples of IEQ measurements collected from over 100 occupants of office spaces at the University of British Columbia in 2019. Bayesian logistic regression of the expanded dataset reinforces observations made in our first paper that thermal comfort is correlated to measured values of indoor CO2 concentrations and speech intelligibility, in addition to parameters of temperature and mean-radiant temperature. This paper formulates a new predictive model of thermal comfort, derived from the Bayesian logistic regression of the COPE and UBC datasets, which can be used by building modellers to predict thermal comfort in office settings based on thermal conditions, ventilation rates, and noise levels.

Scientific Innovation and Relevance

(max 200 words)

Several recent studies have identified the multi-perceptual and multi-contextual relationship of thermal comfort - that thermal comfort may be related to other indices of IEQ and vice versa. Our work is one of few studies to evaluate these relationships quantitatively and in a manner that can support future thermal comfort prediction. The buildings sector is facing several conflated challenges, particularly now in a post-COVID-19 world. Energy use should be minimized to support climate change objectives, but indoor air quality and well-being cannot be sacrificed - if anything, it should be improved as well. Our research has suggested that an open plan office with greater acoustic privacy and/or high amounts of fresh air can provide the same level of thermal comfort at higher/lower temperatures than an office with minimal acoustic privacy and ‘typical’ fresh air ventilation rates. Establishing these relationships in a manner in which building designers can account for these effects in building simulation is important. If low-cost interventions such as acoustic dividers can improve the acceptability range of indoor temperatures in office settings, facilities managers can achieve energy savings through warmer summertime temperatures and cooler winter temperatures.

Preliminary Results and Conclusions

(max 200 words)

The Bayesian regression results inferred from the expanded UBC + COPE dataset revealed stronger evidence to suggest that measured indoor CO2 concentrations and speech intelligibility are independently correlated with perceived thermal comfort. The statistical significance of these results is validated using several Bayesian model validation techniques which, in turn, validates the robustness and significance of our prior findings. We synthesize the regression results into polynomial expressions (similar to the PMV-PPD and Adaptive Comfort models) which can in turn be used to predict thermal comfort in office spaces while taking into account non-thermal metrics of Indoor environmental quality. This new model could be used by building performance simulation experts to predict occupants’ thermal comfort in office spaces. We demonstrate how this can contribute to, and also provide obstacles to, identifying potential building energy savings with respect to heating, cooling, and mechanical ventilation, depending on the climate.

Main References

(max 200 words)

S. Crosby, G. Newsham, J. Veitch, and A. Rysanek. Correlations between thermal satisfaction and non-thermal conditions of indoor environmental quality: Bayesian inference of a field study of offices. Energy and Buildings (in review), 2020.

S. Crosby, and A. Rysanek. Extending the Fanger PMV model to include the effect of non-thermal conditions on thermal comfort. Proceedings of eSim Conference, Vancouver, BC, Canada. 2021 (in review).

A. Jamrozik, C. Ramos, J. Zhao, J. Bernau, N. Clements, T. Vetting Wolf, and B. Bauer. A novel methodology to realistically monitor office occupant reactions and environmental conditions using a living lab. Building and Environment, 130 :190–199, 2018.

J. Langevin, J.and Wen and P. Gurian.Modeling thermal comfort holistically: Bayesian estimation of thermal sensation, acceptability, and preference distributions for office building occupants. Building and Environment, 69: 206–226, 2013.

M. Schweiker, E. Ampatzi, M. S. Andargie, R. K. Andersen, E. Azar, V. M. Barthelmes, C. Berger, ..., and L. P. Edappilly. Review of multi-domain approaches to indoor environmental perception and behaviour. Building and Environment, 2020

J. J. McArthur and C. Powell. Health and wellness in commercial buildings: Systematic review of sustainable building rating systems and alignment with contemporary research. Building and Environment 171 (2020): 106635.



15:52 - 16:10

A gap-filling method for room temperature data based on autoencoder neural networks

Antonio Liguori1, Romana Markovic2, Jérôme Frisch1, Andreas Wagner2, Francesco Causone3, Christoph van Treeck1

1E3D - Institute of Energy Efficiency and Sustainable Building, RWTH Aachen University, Mathieustr. 30, 52074 Aachen, Germany; 2Building Science Group, Karlsruhe Institute of Technology, Englerstr. 7, 76131 Karlsruhe, Germany; 3Department of Energy, Politecnico di Milano, Via Lambruschini 4, 20156 Milano, Italy

Aim and Approach

(max 200 words)

The aim of this paper is to investigate the feasibility of autoencoder neural networks for reconstructing the missing indoor air temperature sequences that are obtained from room automation. For that purpose, three deep learning architectures that include feed-forward, 1D-convolutional and long short-term memory (LSTM) denoising autoencoders were implemented to learn the daily indoor air temperature patterns. The sequences of the monitored room automation data were undersampled to 30 minutes’ frequency and the reconstructed gaps in measured data ranged between few hours (10 % of the daily values) and around 22 hours (90 % of the daily values).

The developed models were evaluated using the monitoring data collected in multiple buildings with significant differences in thermal mass and design. Finally, the model’s performance was compared to the baseline models such as linear interpolation and mean inserting.

Scientific Innovation and Relevance

(max 200 words)

Thanks to the growing number of installed meters in buildings (Rätz, 2019), data-driven models have experienced an increasing use in the area of building energy and environmental performance optimization (Ibeigi, 2020), (Zhou, 2020). However, one of the main limitations for data-driven modeling is the presence of errors and missing values in these data sets (Chong, 2016). In the related literature, there is still little relevant research about this issue and, for this reason, the adopted reconstruction techniques often lead to limited models’ performance (Chong, 2016).

In this regard, the proposed autoencoder neural networks for the missing data reconstruction represent a promising approach to fill the latter research gap. The particular novelty of this method is that it benefits from the spatial and temporal correlation of the input features, which can lead to significant performance improvement. This is achieved by relying on the LSTMs for handling the temporal relationships and convolutional units for handling the spatial correlations within the models’ input and output features.

Preliminary Results and Conclusions

(max 200 words)

The results showed, that the temporal (day-to-day) correlation have more predictive power, when compared to the spatial correlation (dimensions within the same day). The proposed autoencoder neural network could effectively reconstruct missing indoor air temperature data with accuracy over 90 % in terms of root mean squared error. Furthermore, the models’ performance did not drop with the increased duration of the missing sequences. Accordingly, the obtained results confirmed the findings from Fan et at. (2018) - namely, autoencoder neural networks can capture patterns of building energy and control data, which represents a significant practical potential for the inclusion of these models in the real-time building control. Comprehensive results and further conclusions will be presented in the main paper.

Main References

(max 200 words)

Chong et al., Imputation of missing values in building sensor data, ASHRAE and IBPSA-USA SimBuild 2016 Building Performance Modeling Conference, Salt Lake City, UT (2016).

Fan et al., Analytical investigation of autoencoder-based methods for unsupervised anomaly detection in building energy data, Appl Energy 211 (2018) 1123-1135.

lbeigi et al., Prediction and optimization of energy consumption in an office building using artificial neural network and a genetic algorithm, Sustain Cities Soc 61 (2020) 102325.

Rätz et al., Automated data-driven modeling of building energy systems via machine learning algorithms, Energy Build 202 (2019) 109384.

Zhou et al., Using long short-term memory networks to predict energy consumption of air-conditioning systems, Sustain Cities Soc 55 (2020) 102000.

 
14:40 - 16:10Session W3.8 (Online Track): The role of occupants
Location: Virtual Meeting Room 2
Session Chair: Wangda Zuo, University of Colorado Boulder
Virtual Meeting Room 2 
 
14:40 - 14:58

A synthetic population model for representing occupant behaviors in buildings

Handi Chandra Putra, Tianzhen Hong

Lawrence Berkeley National Laboratory, United States of America

Aim and Approach

(max 200 words)

The current development of occupant behavior research has come to a more elaborate framework of building occupant interaction. Researchers collected behavioral data but often found it a challenge to meet the minimum number of required data points and the data interoperability requirements. Researchers address the first issue with the synthetic population and the latter with data ontologies. The two solutions are complementary to each other. One of the known ontologies, Drivers-Needs-Actions-Systems (DNAs) ontology, has been used by building modelers to describe energy-related occupant behavior[1]. The expansion of DNAs ontology is intended to pave a synthetic occupant population pathway that further its use in multiple applications, including the emerging agent-based modeling (ABM) [2]. The synthetic population approach is useful for detailed characterization of occupant-agent and a group-of-agent in the ABM environment. Previously collected data on occupants, including ASHRAE Thermal Comfort DB II [3], IEA Annex 66 data set [4], drive the synthetic behavior generation. Occupants’ demographic characteristics are drawn from multiple sources, including U.S. decennial census and microdata sample[5], as well as The National Household Travel Survey[6]. Case studies of residential and commercial buildings are used to present the workflow of DNAs framework expansion, synthetic population generation, and agent-based modeling.

Scientific Innovation and Relevance

(max 200 words)

The need for a more detailed occupant behavior modeling is becoming prevalent in the context of human-building interaction. Occupant modelers borrow behavioral theories and models from other established-disciplines in the area. The Theory of Planned Behavior (TPB), for example, describes how social norms, energy usage habits, and economic concern drive the behavior of occupants to adjust thermostat settings in their rooms [7]. Hence, the expansion of DNAs ontology introduces new elements that fall into five categories: socio-economic, geographical location, activities, subjective actions, and individual and collective adaptive actions. The locus of control of individual occupants within the collectivity of occupants is challenging in synthetic population research. Demographers have tried to synthesize individuals and match them with synthesized households. The synthesized individuals and individual-groups are, then, validated with the marginal distribution of real census data and microdata [8]. The synthetic occupant generation follows the DNAs ontology to describe the occupants and uses an integrated population synthesis method of Bayesian network (BN) and multi-level iterative proportional fitting (IPF). The resulting synthetic data represent the probability distribution of a sample of real data.

Preliminary Results and Conclusions

(max 200 words)

The proposed enhancements to the DNAs framework represent occupant behavior in greater detail, which can inform occupant data collection and synthetic occupant data generation efforts. The core components of the framework that draws upon adaptive behavioral constructs, namely Drivers, Needs, Actions, and Systems remain unchanged. The expansion includes geographical location characteristics of an occupant, such as climate zone, urban and rural regions. Relevant energy-related policies in place, as well as infrastructural investments of a municipality, are also behavioral determinants that are attributed to location. Moreover, energy-use behaviors are also varied based on building types; hence, the framework includes the building types. Both statistical construct synthetic occupant populations and reproduce the sample occupant data with well-fitting distributions. The synthetic population model is, then, utilized for running ABM and generating better occupant data for building energy modeling.

Main References

(max 200 words)

[1] T. Hong, S. D’Oca, W. J. N. Turner, and S. C. Taylor-Lange, “An ontology to represent energy-related occupant behavior in buildings. Part I: Introduction to the DNAs framework,” Building and Environment, vol. 92, pp. 764–777, Oct. 2015.

[2] C. Berger and A. Mahdavi, “Review of current trends in agent-based modeling of building occupants for energy and indoor-environmental performance analysis,” Building and Environment, vol. 173, p. 106726, Apr. 2020.

[3] V. F. Licina et al., “Development of the ASHRAE Global Thermal Comfort Database II,” BUILDING AND ENVIRONMENT, vol. 142, pp. 502–512, Sep. 2018.

[4] International Energy Agency, “Energy in buildings and communities program. Annex 66: definition and simulation of occupant behavior in buildings.” [Online]. Available: http://www.annex66.org/.

[5] U. S. Census. Bureau, 2015: http://factfinder2.census.gov.

[6] F. H. A. (FHWA), “National Household Travel Survey,” 2017: https://nhts.ornl.gov/.

[7] E. L. Hewitt, C. J. Andrews, J. A. Senick, R. E. Wener, U. Krogmann, and M. Sorensen Allacci, “Distinguishing between green building occupants’ reasoned and unplanned behaviours,” Building Research & Information, vol. 44, no. 2, pp. 119–134, Feb. 2016.

[8]K. Müller, “A generalized approach to population synthesis,” 2017.



14:58 - 15:16

How do buildings adapt to changing occupancy? A natural experiment

Brodie W. Hobson1, Tareq Abuimara1, H. Burak Gunay1, Guy R. Newsham2

1Department of Civil and Environmental Engineering, Carleton University; 2Construction Research Centre, National Research Council Canada

Aim and Approach

(max 200 words)

Modern office buildings regulate their indoor climate through a series of conservative setpoints and equipment schedules that are chosen early in the design phase to ensure adequate indoor air quality at maximum occupancy. However, the occupancy of most modern office buildings rarely exceeds 50%, yet operations are seldom optimized for actual occupancy. This lack of adaptability to changing occupancy exacts a toll on buildings’ energy use by providing excessive building services in an inefficient manner. Largely vacant offices buildings left in the wake of the recent COVID-19 pandemic present a natural experiment to evaluate the extent of this problem in an extreme case. Data from the building automation systems of several office buildings were collected before, during, and after the exodus of office workers to determine the impact this change in occupancy had on building energy use, and to establish a timeline for any operational changes to ventilation, temperature setpoints, and artificial lighting. Wi-Fi data were collected to estimate the occupancy of each building over this period for comparison. Three-point univariate changepoint models were employed to estimate the change in energy use pre- and post-pandemic. Design and operational challenges to buildings’ adaptability to occupancy are identified.

Scientific Innovation and Relevance

(max 200 words)

The novel case study presented capitalizes on the unique oppourtunity created by the COVID-19 pandemic to identify current obstacles that hinder the adaptability of commercial building HVAC and artificial lighting systems to variable occupancy. The issue of adaptability is sure to become more prevalent in the global commercial building stock with persistent habits such as teleworking evolving at an accelerated pace. This unprecedented natural experiment also allows for the collection of data in buildings with near-zero occupancy on a much larger timescale than ever before, which will generate new insights into the role of occupants in buildings’ energy use. Operational strategies and changes made by operators after the onset of the pandemic – and the impact on building energy use – are discussed and quantified. The lag time between recommended changes and the implementation of these interventions in building automation systems is characterized and examined in the broader context of day-to-day building operations. Recommendations are put forth to help inform design decisions such as equipment sizing, as well as new simulation-based design approaches that take this variable occupancy into account to help improve buildings’ adaptability to variable occupancy in extreme cases and during day-to-day operations alike.

Preliminary Results and Conclusions

(max 200 words)

Preliminary data shows that the energy use was largely unchanged for several weeks after the COVID-19 lockdown began, even though many of the buildings’ occupancies had dropped dramatically in a single day, and to near-zero in less than one week. While a small decrease in energy use was observed due to reduced plug-in equipment and lighting loads in the initial weeks, operating schedules and temperature setpoints were largely unchanged for months after the initial lockdown. The overall energy use of many buildings increased after the onset of the pandemic as new ventilation requirements with higher outdoor air fractions were introduced for health purposes. With the current state of operational practices, buildings are not adaptable to changes in occupancy. While a global pandemic is an extreme case of variable occupancy, changes to system-level equipment schedules and setpoints to optimize energy use for zero occupants should be comparatively simple to the changes required for optimizing more numerous zone-level systems for more subtle changes in occupancy during typical operations. If the additional savings made possible by more granular occupancy-centric controls are to be realized post-pandemic, significant changes to how buildings are designed, simulated, and operated are needed.

Main References

(max 200 words)

F. Haldi and D. Robinson, “The impact of occupants’ behaviour on building energy demand,” J. Build. Perform. Simul., vol. 4, no. 4, pp. 323–338, 2011.

H. B. Gunay, “Improving energy efficiency in office buildings through adaptive control of the indoor climate,” Carleton University, 2016.

H. B. Gunay, M. Ouf, G. Newsham, and W. O’Brien, “Sensitivity analysis and optimization of building operations,” Energy Build., vol. 199, pp. 164–175, 2019.

H. B. Gunay, W. O’Brien, I. Beausoleil-Morrison, and B. Huchuk, “On adaptive occupant-learning window blind and lighting controls,” Build. Res. Inf., vol. 42, no. 6, pp. 739–756, 2014.

I. E. Bennet and W. O’Brien, “Office building plug and light loads: Comparison of a multi-tenant office tower to conventional assumptions,” Energy Build., vol. 153, pp. 461–475, 2017.

M. Ouf, W. O’Brien, and H. B. Gunay, “On quantifying building performance adaptability to variable occupancy,” Build. Environ., vol. 155, no. February, pp. 257–267, 2019.

W. O’Brien et al., “Introducing IEA EBC Annex 79: Key challenges and opportunities in the field of occupant-centric building design and operation,” Build. Environ., p. 106738, 2020.



15:16 - 15:34

Investigating thermostat setpoint preferences in Canadian households

Karthik Panchabikesan1, Mohamed Ouf1, Ursula Eicker1, Guy Newsham2, Heather Knudsen2

1Concordia University, Montreal, QC, Canada; 2Construction Research Centre, National Research Council of Canada, Ottawa, Canada

Aim and Approach

(max 200 words)

Unlike commercial building occupants, residential dwellers have more control over their indoor environment as they often have direct and sole access to thermostats. However, despite the diversity in their indoor temperature preferences, most building energy simulations, codes and standards assume identical thermostat setpoints for all residential buildings. To this end, this study aims to demonstrate the variations in temperature setpoints across Canadian households by analyzing thermostat data collected from ~13,000 residential buildings. The specific objectives of this study are to (1) determine the average heating, and cooling thermostat setpoints in residential buildings, (2) rank the importance of different attributes that influence setpoint preferences, and (3) extract distinct heating and cooling setpoint profiles in residential buildings.

Multiple analysis approaches were used in this study. First, statistical methods were used to estimate the average thermostat setpoints in different provinces. Then, a random forest ensemble learning model was used to rank the relative importance of different attributes on average heating and cooling setpoint temperatures. Finally, the k-Shape clustering technique was used to extract distinct daily heating and cooling setpoint temperature profiles from ~13,000 Canadian homes.

Scientific Innovation and Relevance

(max 200 words)

Studies indicate that residential buildings are responsible for 33% of total electricity use in Canada, and space conditioning (which is controlled by thermostats) accounts for 64% of their energy use. Therefore, occupants’ thermostat setpoint preferences significantly influence buildings’ energy use and play a vital role in the efficient operation of HVAC systems. As thermostat setpoint assumptions are critical inputs for building performance simulations, the diversity in occupants’ preferences across different climate zones and household characteristics should be accounted for to improve the simulation accuracy. Previously, data on occupants’ actual thermostat setpoint preferences were not widely available and obtained primarily through self-reporting via surveys. However, today’s new generation of smart thermostats enables centralized data collection and sharing at large scales, which paves the way for investigating temperature setpoint preferences, and variations in thermostat settings (concerning several factors such as location, building type, age, etc.) in thousands of residential buildings at once. Such data analysis provides an unprecedented opportunity for re-visiting fixed/simplistic assumptions related to thermostat setpoint schedules in building energy simulations to better reflect operational parameters in actual buildings.

Preliminary Results and Conclusions

(max 200 words)

The results obtained in this study were compared with the building energy codes and standards and differences up to ~3°C were found between the code assumptions and the present study. Moreover, in building energy codes and standards, only daytime and nighttime thermostat setpoint temperatures are provided, ignoring the common practice of setting a different daytime setpoint when occupants are away from home. In this context, assuming appropriate thermostat setpoints considering more typical current occupant schedules is recommended to increase the accuracy of the building simulations. The random forest model results suggest that building energy code provisions might consider different setpoint assumptions based on climatic zones and building characteristics. The analysis of daily setpoint profiles indicates significant variations within households, which were grouped into four main clusters for heating and cooling setpoint temperature, respectively. The majority of these clusters show a daytime temperature setback in residential buildings which is rarely accounted for in building energy codes and standards. Overall, the results presented in this study could be a significant input to updating temperature setpoint assumptions used in the building energy codes, and in energy simulations considering occupant preferences in residential buildings.

Main References

(max 200 words)

1. Huchuk, B., O'Brien, W., and Sanner, S. 2018. A longitudinal study of thermostat behaviors based on climate, seasonal, and energy price considerations using connected thermostat data. Building and Environment, 139:199-210.

2. National Research Council Canada, 2017, National Energy Code of Canada for Buildings 2017. Ottawa, ON.

3. Paparrizos, J. and Gravano, L. 2015. k-shape: Efficient and accurate clustering of time series. In Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, 1855-1870.

4. Peffer, T., Pritoni, M, Meier, A., Aragon, C., and Perry, D. 2011. How occupants use thermostats in homes: A review. Building and Environment, 46(12):2529-2541.

5. Ren, X., Yan, D., and Hong, T. 2015. Data mining of space heating system performance in affordable housing. Building and Environment, 89:1-13.

6. Santin, O.G., Itard, L., and Visscher, H. 2009. The effect of occupancy and building characteristics on energy use for space and water heating in Dutch residential stock. Energy and buildings, 41(11):1223-1232.



15:34 - 15:52

Use of district energy modelling and stakeholder engagement in developing decarbonisation strategies

Susan Pierce1,2, Lorenzo De Donatis2, Fabiano Pallonetto3, Giovanni Tardioli2

1University College Dublin; 2Integrated Environmental Solutions Ltd.; 3IVI Institute - Maynooth University

Aim and Approach

(max 200 words)

Decarbonisation of urban areas will play a vital role in tackling climate change and meeting future carbon emission reduction targets. Densely populated districts, towns and cities are among the most challenging to develop sustainably. This study aims to model and calibrate the largest university campus in Ireland, namely the University College Dublin (UCD), including the adjacent urban community area and drive it through a full decarbonisation pathway by 2050, analysing several possible scenarios focused on the electricity and heating sectors. First, a virtual model of the whole campus, together with its electricity and heating networks, have been created and calibrated using time-series metered data and building management system (BMS) data for the whole 2019; then, future development scenarios have been explored to identify the optimum pathway for decarbonisation, addressing possible changes in the control strategies of existing plants as well as the addition of new assets and renewable energy systems.

Scientific Innovation and Relevance

(max 200 words)

Merging the goals of different stakeholders, objectives and budgets is one of the main challenges to face in this process; simulation at urban scale can help overcoming this by driving decision-makers towards justified routes by leveraging the uncertainty of specific choices. The hybrid approach used for the analyses has given the work the possibility to merge real and simulated data through the interaction of various pieces of software communicating together in order to give strength and reliability to the future development scenarios, being based on a virtual baseline model which behaviour is accurately matching the one of the real campus.

Preliminary Results and Conclusions

(max 200 words)

The modeling of both the thermal and electricity networks enabled the evaluation of the current energy and carbon footprint of the campus, together with the quantification of the impact of possible future developments on carbon dioxide emissions. The analysis concludes that the campus can achieve a 10% reduction in carbon dioxide emissions without the need to install new generation units. The introduction of new biomass combined heat and power unit would increase this reduction to 17% compared to the baseline. Coupling this with the installation of 3 MW of solar photovoltaic, the calculated campus potential, a total reduction of 26% can be achieved.

Main References

(max 200 words)

• Capros, P., Paroussos, L., Fragkos, P., Tsani, S., Boitier, B.,Wagner, F., Busch, S., Resch, G., Blesl, M. and Bollen, J. (2014), `Description of models and scenarios used to assess European decarbonisation pathways', Energy Strategy Reviews 2(3-4), 220-230.

• Horan, W., Shawe, R., Moles, R. and O'Regan, B. (2019), `Development and evaluation of a method to estimate the potential of decarbonisation technologies deployment at higher education campuses', Sustainable Cities and Society 47(January), 101464.

• Kowalski, K., Stagl, S., Madlener, R. and Omann, I. (2009), `Sustainable energy futures: Methodological challenges in combining scenarios and participatory multi-criteria analysis', European Journal of Operational Research 197(3), 1063{1074.

• Oh, Y. K., Hwang, K. R., Kim, C., Kim, J. R. and Lee, J. S. (2018), `Recent developments and key barriers to advanced biofuels: A short review', Bioresource Technology 257(February), 320-333.



15:52 - 16:10

Investigating the correlation dynamism between WiFi connection counts and camera-based occupancy counts

Nastaran Alishahi, Mohamed M. Ouf, Mazdak Nik-Bakht

Concordia University

Aim and Approach

(max 200 words)

Despite the large variations in building occupancy patterns, operation of the heating, ventilation, and air conditioning (HVAC) systems typically assumes a full or near full occupancy. Systems and control sequences that provide demand-controlled ventilation (DCV) aim to address this issue by adjusting building operations based on the real-time occupancy estimates. However, these systems typically rely on measured data such as CO2 sensors as a proxy for occupancy, which presents several limitations, namely significant cost, maintenance requirements, and inherent inaccuracies. Therefore, obtaining accurate real-time building occupancy information using non-intrusive and low-cost approaches offers great potentials to optimize the operation of HVAC systems.

This study aims to investigate the evaluation of building occupancy through the analysis of WiFi counts as a proxy and validate this approach using camera-based image recognition counters. Specific objectives of this study include (i) validating the relationship between these two data streams to establish a correlation between WiFi counts and actual building occupancy; and (ii) developing predictive models to predict daily occupancy patterns including peak occupancy, arrival and departure times, from the WiFi traffic data. Several clustering and regression methods were applied to WiFi and camera-based counts from a library building in Montreal, to achieve these objectives.

Scientific Innovation and Relevance

(max 200 words)

Although WiFi counts have been previously proposed and tested as a proxy for real-time building occupancy, validation with ground truth actual occupant counts has been fairly limited. Since obtaining ground truth occupancy count data is challenging, many studies typically relied on short-term manual counting that can be costly, intermittent, inaccurate, and time-consuming. To this end, this study relied on using camera-based occupancy counters to establish a continuous data stream for validating the correlation between WiFi counts and actual building occupancy. Two different types of counters were used to evaluate the actual occupancy, i.e. optical and thermal sensors. In this regard, after testing the accuracy of the counters through manual counting at random points over time, we considered the readings from these counters as the ground reference values. We employed various statistical analysis methods to identify correlations between the WiFi traffic and actual occupancy counts.

Once this relationship between WiFi and occupant counts was established, WiFi count data can be collected non-intrusively at low cost (i) to estimate building occupancy patterns including peak occupancy as well as arrival and departure times for scheduling HVAC system operations, and (ii) to utilize real-time occupancy information to operate building systems, such as DCV, accordingly.

Preliminary Results and Conclusions

(max 200 words)

Preliminary results show a strong correlation between camera-based counts and the number of WiFi connections on different days. Various linear correlation methods, as well as statistical tests, were used to investigate such correlations. K-means clustering was then employed to identify clusters of typical daily occupancy patterns based on WiFi counts. Four clusters were identified with peak occupancy ranging between 1,000 and 1,800 people, representing different occupancy patterns on Fridays, weekends, and two clusters for the other four weekdays. Seasonality effects were identified on the patterns of occupancy over the weekdays/weekends, which were contributed to the fact that the library belongs to an educational organization. Multiple linear regression models developed for each cluster to predict peak occupancy, earliest arrival, and latest departure times, reached an R2 ranging between 80%-90% in different clusters.

Main References

(max 200 words)

Ashouri, A., Newsham, G. R., Shi, Z., & Gunay, H. B. (2019). Day-ahead Prediction of Building Occupancy using WiFi Signals. 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE), 1237–1242. https://doi.org/10.1109/COASE.2019.8843224

Hobson, B. W., Gunay, H. B., Ashouri, A., & Newsham, G. R. (2020). Clustering and motif identification for occupancy-centric control of an air handling unit. Energy and Buildings, 223, 110179. https://doi.org/10.1016/j.enbuild.2020.110179

Hobson, B. W., Lowcay, D., Gunay, H. B., Ashouri, A., & Newsham, G. R. (2019). Opportunistic occupancy-count estimation using sensor fusion: A case study. Building and Environment, 159, 106154. https://doi.org/10.1016/j.buildenv.2019.05.032

Ouf, M. M., Issa, M. H., Azzouz, A., & Sadick, A.-M. (2017). Effectiveness of using WiFi technologies to detect and predict building occupancy. Sustainable Buildings, 2, 7. https://doi.org/10.1051/sbuild/2017005

Wang, Y., & Shao, L. (2018). Understanding occupancy and user behaviour through Wi-Fi-based indoor positioning. Building Research & Information, 46(7), 725–737. https://doi.org/10.1080/09613218.2018.1378498

Wang, Z., Hong, T., Piette, M. A., & Pritoni, M. (2019). Inferring occupant counts from Wi-Fi data in buildings through machine learning. Building and Environment, 158, 281–294. https://doi.org/10.1016/j.buildenv.2019.05.015

 
14:40 - 16:10Session W3.9 (Online Track): Buildings paving the way for the energy transition
Location: Virtual Meeting Room 3
Session Chair: Ivan Oropeza-perez, Universidad de las Americas Puebla
Virtual Meeting Room 3 
 
14:40 - 14:58

Modelica-json: Transforming energy models to digitize the control delivery process

Michael Wetter1, Jianjun Hu1, Anand Prakash1, Paul Ehrlich2, Gabe Fierro3, Milica Grahovac1, Marco Pritoni1, Lisa Rivalin4, Dave Robin5

1Berkeley Lab, Berkeley, CA; 2Building Intelligence Group, Portland, OR; 3University of California at Berkeley, Berkeley, CA; 4Facebook, Menlo Park, CA; 5BSC Softworks, Atlanta, GA

Aim and Approach

(max 200 words)

The Modelica Buildings library is used for composing HVAC and control models in the Spawn of EnergyPlus and the OpenBuildingControl project. These models contain a substantial amount of information about HVAC systems and control sequences.

This paper introduces a software that parses Modelica-based HVAC and control models to generate documents that aid in building procurement, construction, commissioning and operation. Generated documents include:

- A list of control sensors, actuators and points for use by control providers to bid on a project.

- A JSON representation of the control sequence for use as input to a process that translates the control sequences to an implementation specific to the selected control product line.

- An English language description of the control sequence for the control provider and the building operator.

- A semantic model, using the Brick data model, that aids in deploying data analysis applications and configuring building diagnostics and FDD tools.

This work, through the use of CDL, will complement ASHRAE's Standards for Communication (Standard 135, BACnet) and Semantic Interoperability (Standard 223P) with a new Standard for expressing the control logic. It will also provide a path to reuse design data to create models using ASHRAE Standard 223P (http://www.bacnet.org/WG/SI/index.html).

Scientific Innovation and Relevance

(max 200 words)

The scientific innovation lies in the combination of a declarative model of the HVAC system (Modelica) and the use of control sequences expressed in the Control Description Language CDL [Wetter et al., 2018] to aid the digitization of the building control delivery process, and to enable the evaluation and optimization of control sequences.

Current practice involves the HVAC designer writing a verbose description of the control sequences, which a project technician interprets to write code for deployment of the sequence in a proprietary control system. This is followed by a manual process to validate and confirm the operation without the quality control procedures commonly used in modern software development. As a result, the performance of these sequences is highly dependent on programmer skills, programmer understanding of the building systems, proper commissioning and timely update in case of operational changes [Pritoni et al, 2020]. The presented process can allow manufacturers to program and test sequences centrally and distribute them to installers [Paliaga et al. 2020], who are only required to take simple configuration steps.

This presentation will focus on the tools that extract control sequences and their semantic information for integration in such a digitized control delivery process.

Preliminary Results and Conclusions

(max 200 words)

A CDL-to-JSON translator and a process which produces English language documentation (HTML or Word) from a JSON representation have been developed. A prototype translator from CDL to the commercial control product line EIKON of Automated Logic Control has also been developed. A translator from Modelica and its CDL subset to Brick [Balaji et al, 2016], a semantic model that is used as input to the development of ASHRAE Standard 223P,is in development, and preliminary results are expected at the time when the full paper is due.

Advantages of this approach include:

- making energy efficient sequences available to any building, independently from the skill of the contractor

- reducing human errors and commissioning time

- ability to quickly scale advanced sequences to a large number of buildings overcoming constraints related to workforce training

- reduced cost and for the building owner

Main References

(max 200 words)

Michael Wetter, Milica Grahovac and Jianjun Hu. Control Description Language. 1st American Modelica Conference, Cambridge, MA, USA, August 2018.

Bharathan Balaji, Arka Bhattacharya, Gabe Fierro, Jingkun Gao, Joshua Gluck, Dezhi Hong, Aslak Johansen, Jason Koh, Yuvraj Agarwal, Mario Berges, David E. Culler, Rajesh Gupta, Mikkel Baun Kjaergaard, Joern Ploennigs, Kamin Whitehouse.

Brick v1.0 - Towards a Unified Metadata Schema for Buildings.

3rd ACM International Conference on Systems for Energy-Efficient Built Environments (BuildSys), November 2016.

Marco Pritoni, Anand Prakash, David Blum, Kun Zhang, Hwakong Cheng, Gwelen Paliaga, Rui Tang, Jessica Granderson. Advanced control sequences and FDD technology. Just shiny objects, or ready for scale? ACEEE summer study proceeding. 2020. (Accepted )

Paliaga G., Singla R., Snaith C., Lipp S., Mangalekar D., Cheng H. Pritoni M. Re-Envisioning RCx: Achieving Max Potential HVAC Controls Retrofits through Modernized BAS Hardware and Software. ACEEE summer study proceeding. 2020. (Accepted )



14:58 - 15:16

Effect of selected passive cooling measures on overheating in residential buildings in Canada

Michal Bartko, Abdelaziz Laouadi, Michael Lacasse

National Research Council, Canada

Aim and Approach

(max 200 words)

Due to the climate change effects, summer outdoor temperatures are rising with increasing frequencies. Such climatic changes may result in overheating of buildings’ interior spaces, thus causing thermal discomfort and heat-related issues to building occupants such as heat exhaustion, dehydration, heat strokes and even death.

A methodology to evaluate overheating in buildings was developed and overheating was analysed using building simulation tool. EnergyPlus® simulation software with its group of Air Flow Network object was used for this purpose. Archetype building models of several types of Canadian residential buildings were developed, including:

- Midrise Multi Unit Residential Building

- Single family detached house

- Row (town) house

This paper reports on overheating in single detached houses. Simulations were carried out for Ottawa, Ontario, Canada. Weather files for the historical period and seven scenarios of future projections of climate were considered for the simulation to analyse overheating

Scientific Innovation and Relevance

(max 200 words)

The overheating effects were investigated for residential buildings and thermal comfort was evaluated using the index of transient standard effective temperature. Several passive cooling measures were evaluated including:

Building envelope thermal mass (heat capacity)

- light- outside vinyl cladding on wood stud wall

- medium- outside brick veneer on wood stud wall

Construction sets with effective R-values

- old (1980s) R15

- retrofit (2015) R24

- current (2015) R18

- future- net zero R27

Shading

- Exterior rollers/ shutters

- Interior blinds

- Reflective interior blinds

Cooling

- Fully air conditioned

- Partially air conditioned with relaxed cooling set-point

Ventilation

- Mechanical, night ventilation

- Natural, open windows when indoor temperature is higher than the outside temperature and the set-point temperature of 26˚C

- Mixed ventilation, natural and mechanical.

Preliminary Results and Conclusions

(max 200 words)

The results showed that during outdoor extreme heat events, the room temperatures exceed the comfortable levels for extended time periods, thus creating heat stress for occupants. The effectiveness of several passive cooling strategies, such as shading, and ventilation, and trade-off between energy efficiency and building thermal resiliency were evaluated.

The effect of thermal insulation (R value) seems very significant with more insulated buildings more prone to overheating. Increased ventilation proved very efficient in decreasing the indoor air temperature and shortening duration of exposure to high temperatures considerably. This includes both, the night ventilation by opening windows when outdoor conditions allow, as well as mechanical ventilation. Shading by exterior blinds and electrochromic and thermochromic windows decreased the cooling loads by 75, 50 and 40% respectively compared to the commonly used interior blinds.

The modelling results using future climate with anticipated temperature increase of 3.5˚C (intense, year 2081) by year 2100 show increase of the overall cooling loads by 30 to 40%.

Main References

(max 200 words)

ASHRAE 55, (2017) Thermal Environmental Conditions for Human Occupancy

CMHC* (1984), Canadian wood-frame house construction

CMHC* (2013), Canadian wood-frame house construction

Laouadi, A. et al. (2018), Climate resilience of buildings, overheating in buildings- literature review

Laouadi, A. et. al. (2020), Development of reference summer weather years for analysis of overheating risk in buildings. Journal of Building Performance Simulation

NRCan, (2011) Survey of Households Energy Use

Parekh, A. (2005), Development of archetypes of building characteristics libraries for simplified energy use evaluation of houses

*CMHC- Canadian Mortgage and Housing Corporation



15:16 - 15:34

District heating: a practical solution for reducing fossil fuel dependency in Quebec’s remote communities

Annie Pike, Michael Kummert

Polytechnique Montreal, Canada

Aim and Approach

(max 200 words)

For over 100 years, district heating (DH) has been a reliable and economical alternative to individual heating technologies. More recently, the ability to harness alternative forms of thermal energy has made DH a prominent solution for the decarbonization of energy systems. These systems enhance synergies between electrical and thermal energy generation through waste heat recovery and conversion of excess renewable electricity. The aim of the present study is to characterize the potential of DH in the context of Quebec’s remote communities, which currently rely largely on fossil fuels to power and heat their buildings.

This paper first details the procedure used to develop a set of building archetypes appropriate to the region to accurately simulate the hourly heating demand of Whapmagoostui-Kuujjuarapik, the community selected for this study. Next, a series of energy models are developed to represent varying levels of renewable energy integration, with and without DH. These models are used to assess the supplementary fossil fuel reductions enabled by coupling the thermal and electrical grids via a DH network. Simulation results are presented in terms of the financial investment required to achieve a GHG emissions reduction target to highlight the point at which DH becomes economically feasible.

Scientific Innovation and Relevance

(max 200 words)

Reducing fossil fuel dependency in remote communities is an important challenge in Canada and has been the focus of many studies in recent years. However, most of these studies focus entirely on power generation without consideration of the fossil fuel use associated with heating. Where heating solutions are considered, they are typically limited to individual residential systems. The present study demonstrates the strength of community-scale thermal energy infrastructure as a low-carbon alternative. An additional contribution of this paper is the methodology used to quantify the community heating demand. Buildings in remote communities, specifically residential units, have energy-use characteristics that can deviate significantly from “typical” buildings. Energy simulation results from existing building archetypes for cold-climate regions [1] are compared to archetypes created based on building envelope and occupancy-related parameters specific to Whapmagoostui-Kuujjuarapik.

Preliminary Results and Conclusions

(max 200 words)

A set of six archetypes covering 85% of the residential building stock in Whapmagoostui-Kuujjuarapik have been developed and reveal that existing archetypes significantly overestimate the residential heating demand. Initial simulations of the DH model have shown that generator waste heat recovery without any renewable energy source could eliminate over 15% of the combined building energy GHG emissions in Whapmagoostui-Kuujjuarapik. Further simulations that combine DH with wind energy generation indicate that DH is a more efficient solution than battery energy storage for increasing renewable energy penetration, and thereby reducing GHG emissions. The final paper will include a discussion of the economic parameters associated with these findings and present the levelized cost of energy in each scenario for increasing emissions reduction targets.

Main References

(max 200 words)

[1] “Residential Prototype Building Models | Building Energy Codes Program.” [Online]. Available: https://www.energycodes.gov/development/residential/iecc_models. [Accessed: 13-Jul-2020].

[2] E. Wilson, C. E. Metzger, S. Horowitz, and R. Hendron, “2014 Building America House Simulation Protocols,” 2014.

[3] L. Guo et al., “Optimal design of battery energy storage system for a wind-diesel off-grid power system in a remote Canadian community,” IET Gener. Transm. Distrib., vol. 10, no. 3, pp. 608–616, 2016.

[4] Hydro-Québec Distribution, “Suivi sur les causes de la consommation en 2e tranche d’énergie au tarif DN,” 2019.

[5] A. Dalla Rosa, R. Boulter, K. Church, and S. Svendsen, “District heating (DH) network design and operation toward a system-wide methodology for optimizing renewable energy solutions (SMORES) in Canada: A case study,” Energy, vol. 45, no. 1, pp. 960–974, Sep. 2012.

[6] U. Persson and S. Werner, “Heat distribution and the future competitiveness of district heating,” Appl. Energy, vol. 88, no. 3, pp. 568–576, Mar. 2011.

[7] H. Lund, B. Möller, B. V. Mathiesen, and A. Dyrelund, “The role of district heating in future renewable energy systems,” Energy, vol. 35, no. 3, pp. 1381–1390, 2010.



15:34 - 15:52

Quantifying the effect of multiple demand response actions on electricity demand and building services via surrogate modeling

Na Luo, Jared Langevin, Handi Chandra Putra

Lawrence Berkeley National Laboratory, United States of America

Aim and Approach

(max 200 words)

Demand response (DR) and dynamic grid integration of building loads is playing an increasingly important role in ensuring grid reliability and resilience in the face of day-to-day stresses and emergency events [1]. Identifying the potential changes in building demand and indoor services given certain DR strategies may facilitate the real-time decision-making process for building operators who wish to participate in DR programs [2].

In this study, we explore a surrogate modeling approach to predict changes in core building electricity demand and services in office and retail buildings under a given set of outdoor environmental conditions and dynamic DR actions. The surrogate modeling approach consists of the following steps: 1) define assumptions for different DR scenarios and develop DR measures in OpenStudio/EnergyPlus [3]; 2) simulate DR measures across all climate zones, building types and vintages of interest; 3) compile results into synthetic database covering various outcomes; 4) develop simpler regression models of building services and electricity demand using the synthetic database; 5) quantify the effect of multiple DR scenarios on building services and electricity demand. To maximize the flexibility of the developed regression models to future updating in real field settings, each is implemented in a Bayesian inference framework [4].

Scientific Innovation and Relevance

(max 200 words)

A comprehensive set of DR scenarios are designed and simulated in this work across influential office and retail building loads to maximize the relevance of developed models to high-impact DR decision-making in buildings. Specifically, the generated synthetic database covers a wide variety of conditions as listed below, yielding a set of predictive models that can be broadly applied in guiding flexible building operations.

- Six types of DR strategies are simulated - 1) global temperature adjustment (GTA), 2) GTA+pre-cooling, 3) outdoor air (OA) reduction, 4) lighting dimming, 5) plug load reduction (limited to office buildings), and 6) packages of #1-5. For each DR measure, we defined three levels of adjustments - low, moderate and high; and two levels of DR event duration - shorter (e.g., 4 hours) and longer (e.g., 8 hours).

- Two prototypical commercial building types are selected - 1) medium-size office building and 2) standalone retail building - to investigate the effects of DR on building services and electricity demand under different operation modes.

- The simulations are also conducted across 4 prototypical vintages - pre-1980, 1980-2004, 2004 and 2010, as well as 13 climate zones, referring to the ASHRAE climate zone map to capture the potential impact of outdoor environments and local building design codes.

Preliminary Results and Conclusions

(max 200 words)

The surrogate models are able to effectively predict changes in whole building demand as well as indoor temperature, relative humidity, illuminance and CO2 concentration under the different DR scenarios suggested above, across building types and vintages. Models are assessed using several metrics that cover their accuracy and robustness, including R2, Absolute Relative Error (ARE), Mean Absolute Deviation Percentage (MADP), and Variance inflation factor (VIF). Moreover, by implementing the surrogate models in a Bayesian framework, we are able to quantify the uncertainty in our models’ predictions in a straightforward manner, which is critical for communicating the risk of unacceptable service level changes from DR actions to building operators.

Our models yield important insights on the likely impacts of various DR strategies on building demand, for example: 1) GTA with precooling exerts the most obvious effect on demand shedding among five individual DR strategies, while OA reduction has the least impact; 2) the costs of pre-cooling in older buildings is notably greater than in newer buildings - particularly for the office; and 3) the potential demand shedding from DR packages is less than the direct summation of the savings from each measure, suggesting meaningful interactions across the operation of these measures when packaged.

Main References

(max 200 words)

[1] Motegi, N., Piette, M. A., Watson, D. S., Kiliccote, S., & Xu, P. (2007). Introduction to Commercial Building Control Strategies and Techniques for Demand Response.

[2] Yin, R., Kara, E. C., Li, Y., DeForest, N., Wang, K., Yong, T., & Stadler, M. (2016). Quantifying flexibility of commercial and residential loads for demand response using setpoint changes. Applied Energy, 177(September), 149–164. https://doi.org/10.1016/j.apenergy.2016.05.090.

[3] Crawley, D. B., Lawrie, L. K., Pedersen, C. O., & Winkelmann, F. C. (2000). Energy plus: energy simulation program. ASHRAE Journal, 42(4), 49–56.

[4] PyMC Development Team. (2018). PyMC3 Documentation. Available online: https://docs.pymc.io/.



15:52 - 16:10

Optimizing price-informed operation of a battery storage system in an office building

Xuechen Lei, Ellen Franconi, Yunyang Ye

Pacific Northwest National Laboratory, United States of America

Aim and Approach

(max 200 words)

Many of tomorrow’s building technologies go beyond efficiency considerations and target increased load flexibility. Such demand flexibility measures (DFMs) and behind-the-meter distributed energy resources (DERs) can postpone or reduce electric load based on a price or other grid signal, which supports achieving grid-interactive efficient buildings (GEB) and energy resilience. However, considering DFMs and DERs in energy policy creates a new set of analysis challenges that needs to be addressed. For example, new prescriptive efficiency measures amended to current US model energy codes historically have been evaluated using an average, blended electricity rate, which accounts for demand charges. Post 2019, new code proposals can be evaluated using a representative time-of-use (TOU) rate. While this is a step in the right direction, more sophisticated analysis methods are needed to consider a variety of TOU rates and make impact assessments that account for price-informed control. To address these needs, this study couples an office prototype building simulation model with varying-in-sophistication battery storage operating strategies for different electricity TOU rates. The analysis compares the energy savings impact of operating a battery storage system following simpler rule-of-thumb methods versus a semi-optimized priced-informed operation.

Scientific Innovation and Relevance

(max 200 words)

The effective evaluation of cost effectiveness for capital-intensive demand flexibility measures, such as energy storage technologies, requires a customized approach that accounts for variations in TOU tariffs that occur across utilities and regions. While advanced optimization methods may be warranted when assessing multiple interactive systems and dynamic pricing, energy policy studies do not usually require the same level of detail. Instead, they need to make performance assessments across multiple building types and climate zones, while maintaining enough customization to address variations in the most influential parameters. This paper investigates such considerations for battery storage to develop a practical and efficient analytical approach to be applied in energy code development. The research explores using a heuristic method to develop a semi-optimized, customized strategy that is practical to integrate into whole-building simulation analysis to assess national savings potential. Its heuristic-based battery operation strategy also has the potential for implementation in a building energy management and control system. To verify the effectiveness of the proposed semi-optimized approach, we compare it to two simpler rule-of-thumb battery operation strategies. We conduct the analysis for two demand-based TOU rates applied to a large and medium office building in three locations representing hot-humid, mixed-humid, and cool-humid conditions.

Preliminary Results and Conclusions

(max 200 words)

Implementing the simpler rule-of-thumb methods instead of a semi-optimized approach reduces annual electricity cost savings and, therefore, the cost effectiveness of the battery system investment. For the ASHRAE TOU rate, the results show that a more optimized approach provides additional savings to be ~ $5 - $8 / kWh battery capacity. For the ConEd TOU rate, the additional savings are ~ $5 - $10 / kWh. Perhaps of equal importance though, is the impact that a simplified approach has on battery cycling and its life. For example, Li-Ion battery system cost is estimated at $360/kWh capacity with the battery storage cost comprising $190/kWh of the total (Mongrid et al 2019). Levelizing capacity cost over a 10-year life indicates a $19/kWh year cost. Comparing this normalized first cost to the incremental savings of the semi-optimized solution, as well as the additional benefit realized from improving the battery life by 40% to 70%, indicates a substantial added benefit for utilizing a semi-optimized, customized TOU approach for evaluation battery storage impact.

Main References

(max 200 words)

• Franconi, E, J Lerond, C Nambiar, M Rosenberg, R Hart, and D Kim. 2020. Realizing Demand Flexibility with Commercial Building Energy Codes. PNNL-29604. Pacific Northwest National Laboratory. Richland, WA. (publication pending)

• VanCutsem, O, M Kayal, D Blum, and M Pritoni. 2019. “Comparisons of MPC Formulations for Building Control under Commercial Time-of-Use Tariffs.” 2019 IEEE PowerTech Milan.

• Panagiota, G, K Foteinski, A Heller, and C Rode. 2017. “Intelligent Scheduling of a Grid-Connected heat Pump in a Danish Detached House.” Proceedings from the 15th IBPSA Conference, San Francisco California. August 7-9, 2017.

• Luo, N, T Hong, H Li, R Jia, and W Weng. 2017. Data Analytics and Optimization of an Ice-Based Energy Storage System for Commercial Buildings. Lawrence Berkeley National Laboratory. Berkeley, CA.

• Lauro, F, F Moretti, A Capozzoli, and S Panzieri. 2015. “Model Predictive Control for Building Active Demand Response Systems.” The 7th International Conference on Sustainability in Energy and Buildings. Madeira, Portugal. May 16 – 19, 2017.

 
16:10 - 16:40Short break
Location: Concert Hall - Foyers
Concert Hall - Foyers 
16:40 - 17:10IBPSA Fellows & Awards
Location: Concert Hall - Concertzaal
Session Chair: Michael Kummert, Polytechnique Montréal
Concert Hall - Concertzaal 
17:10 - 18:00Keynote: Are “Low-Tech” buildings like the ‘2226’ a solution towards climate neutrality? by Lars Junghans - Associate Professor at the University of Michigan's Taubman College of Architecture and Urban Planning
Location: Concert Hall - Concertzaal

This keynote lecture will be followed by the Student Modelling Competition Award.

Concert Hall - Concertzaal 
18:00 - 18:30Keynote: Thoughts of leading Industry in the heart of the energy transition, by Leonie Assheuer, EU Affairs Manager at Viessmann
Location: Concert Hall - Concertzaal
Concert Hall - Concertzaal 
18:30 - 19:00Short Break
 
19:00 - 19:10Opening evening session by Dirk De Fauw, Mayor of Bruges
Location: Concert Hall - Concertzaal
Concert Hall - Concertzaal 
19:10 - 19:45Keynote: Sustainable architecture is a conscious and sound approach, by Nguyen Hoang Manh - founder of MIA Design Studio, Vietnam
Location: Concert Hall - Concertzaal
Concert Hall - Concertzaal 
19:45 - 20:10Keynote: Vision of a leading global engineering company, towards transforming society together, by Daan Ongkowidjojo (SWECO)
Location: Concert Hall - Concertzaal
Concert Hall - Concertzaal 
20:10 - 21:30Food for body - Networking dinner
Location: Concert Hall - Foyers
Concert Hall - Foyers 
21:30 - 23:00Food for soul - concert: young talents ... promising a bright future ahead
Location: Concert Hall

performed by Emmy d'Arc, Sam De Nef and band

Concert Hall 
Date: Thursday, 02/Sept/2021
8:30 - 10:00Session T1.1: Practice and industry related case studies
Location: Cityhall (Belfry) - Room 1
Session Chair: Mathias Bouquerel, EDF R&D
Session Chair: Jeroen Van der Veken, BBRI
Cityhall (Belfry) - Room 1 
 
8:30 - 8:48

Assessing building envelope thermal performance using in-situ measurements

Jade Deltour1, Karel De Sloover1, Sebastien Pecceu1, Nicolas Heijmans1, Geert Bauwens2

1BBRI, Belgium; 2KULeuven, Belgium

Aim and Approach

(max 200 words)

There are two ways to evaluate a building's energy performance: by calculation or by benchmarking its energy consumption. The calculations have the advantage of being independent of the actual climate and user's preferences, but have the disadvantages to not take into account (not at all or not enough) the quality of the works and aspects not covered by the calculations procedures. It is just the opposite for the benchmarking of consumptions : they include the quality of the works but are not climate and user independent, so cannot be qualified of "building" performance.

Nowadays, in-between solutions are being developed, to take the advantages of both approaches without having their inconvenient. Some focus on the building envelope with a test called "co-heating", that takes as long as 15 days, which is too long. Other use very long term monitoring of consumptions and indoor conditions, and to extract a climate and user independent energy performance among this big amount of data. In both cases, the development of those new techniques requires the intensive use of building simulations.

Building simulation have been used to develop a short (≈ 5 days) dynamic co-heating test to measure the heat loss coefficient (HLC) of a building.

Scientific Innovation and Relevance

(max 200 words)

To select the most reliable protocol, we analysed existing and new protocols based on virtual datasets generated with a simple building simulation software (CAPSOL).

A protocol is a combination of a data collection process and a data analysis process. In the "regular co-heating protocol" the data is collected over a span of 2 weeks, while the building is thermostatically heated to approximately 25 °C (at least 10 °C higher compared with the outdoor temperature). Then, data is analysed through linear regression.

In order to reduce the measurement duration, there are two possible options. First, test conditions can be varied by periodically toggling the heating system on and off. Secondly, more advanced data analysis methods can be applied, using autoregressive with exogenous input (ARX) models or state space models (RC network) solved using differential equations.

The flexibility offered by building simulations allowed the evaluation of different measurement conditions (duration, heating excitation and building typology) combined with various analysis methods. More than 100 protocols and over 2.000 virtual data sets were generated. These measurement protocols (virtually generated) were then evaluated based on accuracy and reproducibility of results.

Preliminary Results and Conclusions

(max 200 words)

This work would not have been possible without the use of virtual data. Simulations allowed us to test a lot of measurements protocols on different typologies, while also giving us a first idea of the reproducibility of these measurements.

The combination of a heating excitation according to a PRBS signal using a state space model for the data analysis seems to be the most stable tested protocol and allows the test duration to be reduced to 5 days (rather than 15 days for a regular co-heating test). Simulations highlighted the interest to limit the impact of the sun during measurements. Moreover, the building typology clearly impacts the results: it is more difficult to obtain an accurate and reproducible result as the insulation level of the building increases. Depending on the typology, the reproducibility varies between +/- 10% to +/- 20%. Finally, the selected protocol was applied on 6 new houses, the results of the experimental campaign were consistent with the values predicted by calculation. However, for these 6 cases, the calculated HLC under evaluated the measured HLC by approximately 14%.

Main References

(max 200 words)

[1] CEN-TC89, N2044, Draft Standard from WG13 TG 5,Thermal performance of buildings – In-situ testing of completed buildings - Part 1: Data collection for whole building aggregate heat loss test

CEN-TC89, N2046, Draft Standard from WG13 TG 5, Thermal performance of buildings – In-situ testing of completed buildings - Part 2: Steady-state data analysis for whole building aggregate heat loss test

[2] J. Wingfield, D. Johnston, D. Miles-Shenton, M. Bell, Leeds Metropolitan University, Whole House Heat Loss Test Method (Coheating), (2010)

[3] G. Bauwens, S. Roels, PhD Theses, In Situ Testing of a Building's Overall Heat Loss Coefficient - Embedding Quasi-stationary and Dynamic Tests in a Building Physical and Statistical Framework, (2015)

[4] International Energy Agency, EBC Annex 58, Report of Subtask 3, part 2 :Thermal performance characterization using time series data – statistical guidelines,

[5] S. Thébault, R. Bouchié, En. & Build., Refinement of the ISABELE method regarding uncertainty quantification and thermal dynamics modelling, 178, 182–205, (2018)

[6] E.Mangematin, G. Pandraud, D. Roux, C. R. Physique, Quick measurements of energy efficiency of buildings , Volume 13, Issue 4, 383-390 (2012)

[7] K. R. Godfrey. Correlation methods. Paper, International Federation of Automatic Control, London, 1980



8:48 - 9:06

Simulating gentle failure as an approach to building resiliency

Ibone Santiago Trojaola1, Susan Ubbelohde1,2, George Loisos1, Nathan Brown1, Eduardo Pintos1, Santosh Philip1

1Loisos + Ubbelohde, Alameda CA USA; 2University of California, Berkeley CA USA

Aim and Approach

(max 200 words)

Increased frequency of events such as mudslides and wildfires, as well as the potential for earthquakes in California, have pushed projects to consider the building’s resilience during an extended power outage and challenging thermal conditions with climate change. In addition to efforts to move annual performance towards zero energy, teams now look at strategies that maximize passive survivability for an indefinite period of time.

This paper describes the case study of an art-center/residence in California where the project recognized these environmental challenges and extended goals to address potential disasters and climate change scenarios, with time becoming an element in energy performance in response to these events.

Simulation of energy use and thermal comfort with a focus on passive survivability helped defining the project targets, developing an implementation plan and sizing the systems. Modeling results enabled stakeholders to make informed decisions and define expectations for a range of scenarios.

This case study includes an energy generation system consisting of several photovoltaic arrays and an energy storage battery system. In addition to installing these systems, the building was designed to enable the owners to automatically implement progressive resiliency stages managing power consumption and effectively reducing energy use as needed during outages.

Scientific Innovation and Relevance

(max 200 words)

This paper describes a “gentle failure” approach to resilience in the context of multiple potential immediate disasters and long-term weather change. It reframes the idea of future proofing buildings by focusing on adaptability and diversity of strategies rather than oversizing systems or hardening the envelope to respond to more extreme conditions.

Every year the environment shows that resilience is more and more critical for every stage of design. Policies are taking the role of addressing this issue but there are still not many examples of how this research applies to and is integrated into practice. Literature on resiliency typically addresses urban-level planning but not how simulation supports the design process or the methodology of actually implementing potential strategies in practice. Similarly, publications about how to obtain data representing climate change scenarios to be used in building simulations are available but do not describe how to think through this range of possibilities and deal with results to design both the building and the systems in a non-normative manner.

This case study builds on previous research for essential services buildings by detailing the implementation of the resiliency plan with construction for the building scheduled to finish in July 2021.

Preliminary Results and Conclusions

(max 200 words)

Resilience was achieved by including appropriately sized energy production and storage systems but also developing an implementation plan to allow the building to “sail itself” through power outages. Space-by space calculations with specific load and usage profiles based on occupant’s preferences were used to develop energy budgets and design the electrical and mechanical systems for three resiliency stages (normal, reduced and minimal operation).

The envelope design was informed by building performance analysis results both in terms of thermal autonomy and energy use reduction. Using multiple iterations of an energy plus model, a series of design alternatives were tested to understand how the building performs with parametric variations of insulation in the roof and wall assemblies, thermal mass and glazing specifications.

Detailed, multivariable performance data over multi-day periods representing extreme weather events to describe potential future scenarios occurring more frequently due to climate change. The building’s flexibility and adaptation surpasses the needs for zero energy performance and allows the project to be operated after being disconnected from the grid, relying on battery storage and PV panels as sources of energy. A performance monitoring system provides measured data of the actual use profile to revisit assumptions if needed.

Main References

(max 200 words)

1-Roostaie S. et al (2019),‘ Sustainability and resilience: A review of definitions, relationships, and their integration into a combined building assessment framework’ , Building and Environment, Volume 154, May 2019, Pages 132-144

2-Rajkovich N. et al (2019), ‘Climate Change Resilience Strategies for the Building Sector: Examining Existing Domains of Resilience Utilized by Design Professionals’, Article in Sustainability 2019, 11, 2888; doi:10.3390/su11102888

3-Dickinson, R. and Brannon, R. (2016) ‘Generating Future Weather Files for Resilience’, PLEA 2016: 36th International Conference on Passive and Low Energy Architecture.

4-Trogal, K. et al, Architecture and Resilience: Interdisciplinary Dialogues (2018) Taylor & Francis Ltd.

5-Sillmann, J. et al. (2017) ‘Understanding, modeling and predicting weather and climate extremes: Challenges and opportunities’, Weather and Climate Extremes.

Elsevier Ltd, 18(November), pp. 65–74. doi: 10.1016/j.wace.2017.10.003.

6-Santiago Trojaola, I. et al. (2017) ' Simulation in Support of Zero Net Energy and Resilient Design', Proceedings of the 15th IBPSA Conference San Francisco, pp 2333-2341.

7-Brian, R. (2014) “The Principles of Future-Proofing: A Broader Understanding of Resiliency in the Historic Built Environment.” Journal of Preservation Education and Research, vol. 7 (2014): 31–49.



9:06 - 9:24

Energetic self-sufficiency of a greenhouse residence: a dynamic techno-financial feasibility study

Charlotte Verhaeghe1, Mateusz Bobier1, Rik Berens1, Amaryllis Audenaert1, Stijn Verbeke1,2

1University of Antwerp, Belgium; 2VITO, unit Smart Energy and Built Environment, Belgium

Aim and Approach

(max 200 words)

The dependence of high energy performance buildings on external energy supply options can further be reduced by increasing the building's energetic self-sufficiency (ESS), up to the level of complete energy autonomy. A techno-financial analysis is carried out for different stages of ESS, up to the 100% ESS-level, for a greenhouse residence in Belgium. The energy demand, retrieved by means of dynamic whole building simulation, is to a large extent covered by on-site renewable energy sources (RES), combined with a certain capacity of electrical energy storage as a buffer, both sized using external scripts. The financial feasibility of the ESS-variants is evaluated for a variety of both static and dynamic pricing mechanisms under three economic cornerstone scenarios. The results indicate that increased (annual) ESS requires highly oversized on-site RES and energy storage options during most part of the year, thereby making the investment financially unattractive. The hypothesis that the techno-financial feasibility of various ESS-levels is highly dependent on the considered boundary conditions (e.g. end-use, time, spatial -and economic boundaries) is furthermore confirmed.

Scientific Innovation and Relevance

(max 200 words)

While there is a large amount of literature on technical and financial feasibility of (nearly or net) Zero Energy Buildings (ZEBs), there is less research on the comparison of dynamic technical and financial feasibility of the different stages of self-sufficiency towards the off-grid level. In this study dynamic whole building simulation tool EnergyPlus is coupled to external scripts for sizing energy storage technologies in relation to different levels of self-sufficiency. The dynamic- and in the future more realistic and relevant- pricing mechanisms are a direct result of the growing stress on the energy grid, which is increasingly characterized by intermittent renewable energy production. Therefore, it is relevant to analyse the effect of various energy pricing mechanism on the financial feasibility of the building project.

Preliminary Results and Conclusions

(max 200 words)

The hypothesis that the techno-financial feasibility of various ESS-levels is highly dependent on the considered boundary conditions (e.g. end-use, time, spatial -and economic boundaries) is confirmed.

Furthermore, the dynamics of energy demand and generation profiles and energy pricing scenarios have an important effect on both the technical and financial analysis. Simple rules of thumb are not likely to be suitable in early design decisions, which indicates the need for (co-)simulations instead.

The results indicate that it is essential to allow for energy storage to both serve the building and the energy grid. Programmable energy management is furthermore a promising solution to increase financial attractiveness of increased ESS.

In addition, it was found that a zonal model to determine the effects of the greenhouse on the energy demand of the building is more accurate than a single zone model in EnergyPlus.

Main References

(max 200 words)

[1] Marszal AJ, Heiselberg P, Bourrelle JS, Musall E, Voss K, Sartori I, et al. Zero Energy Building - A review of definitions and calculation methodologies. Energy Build 2011;43:971–9. https://doi.org/10.1016/j.enbuild.2010.12.022.

[2] Vale B, Vale R. The new autonomous house: Design and planning for sustainability. Thames & H. London: 2000.

[3] Torcellini P, Pless S, Deru M, Crawley D. Zero Energy Buildings: A Critical Look at the Definition. ACEEE Summer Study Pacific Grove, 2006, p. 15. https://doi.org/10.1016/S1471-0846(02)80045-2.

[4] Kolokotsa D, Rovas D, Kosmatopoulos E, Kalaitzakis K. A roadmap towards intelligent net zero- and positive-energy buildings. Sol Energy 2011;85:3067–84. https://doi.org/10.1016/j.solener.2010.09.001.

[5] Sun Y, Ma R, Chen J, Xu T. Heuristic optimization for grid-interactive net-zero energy building design through the glowworm swarm algorithm. Energy Build 2020;208:109644. https://doi.org/10.1016/j.enbuild.2019.109644.

[6] Georgakarakos AD, Mayfield M, Hathway EA. Battery storage systems in smart grid optimised buildings. Energy Procedia, vol. 151, Elsevier Ltd; 2018, p. 23–30. https://doi.org/10.1016/j.egypro.2018.09.022.

[7] Treado S, Delgoshaei P, Windham A. An Evaluation of Simulation-based approaches for building control system design and integration. Trans Control Mech Syst 2014;3:2544–51.



9:24 - 9:42

Energy prediction under changed demand conditions: robust machine learning models and input feature combinations

Thomas Schranz1, Johannes Exenberger1, Christian Møldrup Legaard2, Ján Drgoňa3, Gerald Schweiger1

1Graz University of Technology, Austria; 2Aarhus University, Denmark; 3Pacific Northwest National Laboratory, USA

Aim and Approach

(max 200 words)

Deciding on a suitable algorithm for energy demand prediction in a building is non-trivial and depends on the availability of data. In this paper we compare four machine learning models, commonly found in the literature, in terms of their generalization performance and in terms of how using different sets of input features affects accuracy. This is tested on a data set where consumption patterns differ significantly between training and evaluation because of the Covid-19 pandemic. We provide a hands-on guide and supply a Python framework for building operators to adapt and use in their applications.

In this paper we investigate approaches to predict hourly electric energy usage of a five-floor, mixed-use academic building at the Graz University of Technology (TUG) accommodating offices, seminar rooms, laboratories and a lecture hall. We compare the performance of models using combinations of previously observed hourly energy consumption, occupancy data (approximated through registrations in the University's resource management system), weather data, features engineered from date and time (time of day, weekday, holiday) and hourly water consumption as input features.

Scientific Innovation and Relevance

(max 200 words)

With this paper, we contribute to the state of the art in building energy forecasting by assessing the performance and the robustness of four machine learning algorithms (linear regression, random forest, fully-connected neural network, and recurrent neural network) with various sets of input features.

We analyze models in terms of their ability to predict short-term energy demand in a building where the consumption patterns differ significantly between training and test data because of the Covid-19 pandemic.

We provide guidelines for practitioners by

* examining how different lookback and prediction horizons influence the accuracy and robustness of the machine learning models for single-step energy demand prediction

* benchmarking models using additional input features, such as weather data, against models predicting future energy demand from past consumption values only.

* examining the potential of integrating water consumption data for data-driven energy prediction.

As a side-contribution, the Python machine learning framework, as well as the data used in the experiments described here is published on Github. This allows researchers and practitioners to reproduce the results presented in this paper and to adapt the framework for their purposes and applications.

Preliminary Results and Conclusions

(max 200 words)

Results show that using features engineered from date and time affects prediction performance most significantly, regardless of the choice of model and lookback horizon. Additionally, we found that simple models, such as linear regression and random forests perform very well both in terms of generalization ability and robustness with respect to the choice of input features and lookback horizon. Especially the random forests showed exceptional generalization performance for all choices of input features.

Conversely, the neural networks performed well when predicting from previous consumption values alone, but were sensible to the choice of inputs. It stands to reason that this issue could be addressed with regularization techniques, such as dropout layers, L1 or L2 regularization. Besides, we found that the choice of input features and the choice of lookback horizons for the neural networks interacted with each other. Consequently, we did not find neural networks models to adequately fulfill the requirement of working well without extensive testing and tweaking.

Main References

(max 200 words)

Bontempi, G., S. Ben Taieb, and Y.-A. Le Borgne(2013). Machine Learning Strategies for Time Se-ries Forecasting.

European Commission and Climate Action DG(2019).Going climate-neutral by 2050: a strategiclong-term vision for a prosperous, modern, com-petitive and climate-neutral EU economy.

Sun, Y., F. Haghighat, and B. C. M. Fung (2020).A review of the-state-of-the-art in data-driven ap-proaches for building energy prediction.

Rätz, M., A. P. Javadi, M. Baranski, K. Finkbeiner,and D. M ̈uller (2019).Automated data-drivenmodeling of building energy systems via machinelearning algorithms.



9:42 - 10:00

Quantification of the cost of oversizing cooling installations in a case study under construction in Vietnam

Pedro Marques, Mathias Vandecasteele, Kien Le Trung, Wim Boydens

Studiebureau Boydens, Belgium

Aim and Approach

(max 200 words)

In countries where energy regulation is rather lax and young, the HVAC design team might lack the incentive to do a careful sizing of the heating and cooling loads in a building. Instead, predefined values in watts per square meter, generous “safety factors” or a combination of both are used.

Oversizing of HVAC installations occurs more often than one would expect - upon site visits in Vietnam, installations with several chillers are seen running one chiller only. In such cases, oversizing did not necessarily translate into malfunctioning on site, for the building occupants felt no issues – no difference in comfort between an oversized installation and a rightly sized one.

However, such design practice will unquestionably end up in a higher capital investment, lower plant efficiency, higher energy and maintenance costs when compared to a more carefully designed installation.

This document compares side-to-side the final figures of a as-built HVAC design with a dynamic cooling load simulation and quantifies the hidden cost of the oversizing for the target building.

Scientific Innovation and Relevance

(max 200 words)

The prevention of oversizing is a fundamental step for more sustainable buildings, as the impact on energy is two-fold: reducing the installation and running costs of cooling plants allows for the difference to be shifted toward more sustainable solutions.

Besides the fundamental role of regulation to enforce compliance with industry-acknowledged norms, dynamic simulations can play a fundamental role as the time and funds invested in knowledge, licenses and experience can largely be offset by the savings in the capital investment on each project.

Preliminary Results and Conclusions

(max 200 words)

In this case study, the estimation of 1.6 million USD, or 40 usd/m² is undervalued, as other cost affecting factors such as net floor area available for rent, cost of oversized technical spaces and ceiling clearance, are not quantified.

The oversizing is a problem that is difficult to identify, and even harder to quantify, but very real. The difficulty is that there might be no signs of discontent:

• The HVAC designer delivered a system that provides air conditioning as requested, and “better installing too much than not enough”.

• The building manager has no major problems running the system. If one chiller goes out of service, plenty of backup is available.

• The design team technical knowledge is insufficient to assess the issue, either because the team lacks experience, or because past experience comes from analogous designs.

• No regulation is enforcing the reporting and benchmarking of the efficiencies of the cooling plant, or the general building consumption.

Main References

(max 200 words)

nothing to declare

 
8:30 - 10:00Session T1.2: Ensuring high quality building simulations
Location: Cityhall (Belfry) - Room 2
Session Chair: Thierry Duforestel, EDF R&D
Session Chair: Filip Jorissen, KU Leuven
Cityhall (Belfry) - Room 2 
 
8:30 - 8:48

Spatial distribution of thermal comfort: a case study in Paris' station

Edouard Walther1, Mateusz Bogdan1, Fanny Peyre2, Christian Inard2

1AREP L'hypercube, France; 2LASIE Université de La Rochelle, France

Aim and Approach

(max 200 words)

In Building Energy Simulation (BES), the environmental variables for thermal comfort such as air velocity, radiant temperature, dry bulb temperature and relative humidity are nodal, meaning a single scalar value is computed for each thermal zone, regardless of their size. This long-used approach is valid for most of the built environment, however it may prove to be inappropriate in specific cases, such as widely open and/or glazed buildings. Radiation and convection being major contributors to the heat balance of the human body (Pickup and De Dear, 2000), the existence of indoor solar fluxes and of significant variations in the air velocity field cannot be overlooked for a proper evaluation of thermal comfort.

Commercial tools lack the spatial distribution of radiant temperature and air velocity fields for the computation of comfort levels in semi-open places. The aim of the present work is hence to provide a detailed distribution of thermal comfort based on an "enriched” nodal approach, with hourly solar distribution and air velocity fields. A proof of concept is proposed under the form of a case study, using the state-of-the-art, open source softwares: energyplus, coupled with Radiance and openFOAM.

Scientific Innovation and Relevance

(max 200 words)

The method presented in (Walther et al. 2019) is chosen for the computation of natural ventilation, using CFD to obtain the detailed pressure boundary conditions. As a by-product, this approach yields a simulation set-up allowing to compute indoor velocity fields within open buildings with a moderate additional effort.

The indoor isothermal velocity field is obtained by transposing the approach of (Delpech et al. 2005) to the indoor environment: the distribution of air velocities is solved with an isothermal k-epsilon model for 12 incident wind directions, with their median meteorological velocity as inlet. Hourly velocities are reconstructed by field interpolation, selecting the closest precomputed fields. The amplitude is determined by means of scaling by the hourly weather data (Delpech et al. 2005).

The long wave contribution to radiant temperature is obtained directly from the nodal value of the BES. The shortwave contribution is calculated the daylight coefficients method, also known as “the Two-Phase" method (Subramaniam 2017).

The PET index (Walther & Goestschel, 2018) is chosen as comfort metric. In order to preserve both temporal and spatial variation of comfort, the Outdoor Thermal Comfort Autonomy (Nazarian et al. 2019) was used for the qualification of comfortable spaces.

Preliminary Results and Conclusions

(max 200 words)

The presented approach allows for the computation of a spatial distribution of comfort indexes in indoor spaces. It provides a better understanding of the causes of local thermal (dis-)comfort, as each of the underlying phenomena (e.g. solar radiation, wind distribution) has been calculated.

The study of the comfort patterns obtained is interesting for architects as it becomes possible to differentiate “sub-zones” of occupation within a given volume and provides information at a higher level of detail than previously available to space designers.

Interestingly, the computation of the OTCA using different thermal comfort indexes yields rather different results.

As a perspective, one could argue that zonal models are a cheaper alternative to computational fluid dynamics. The coupling of such models with energyplus is however numerically challenging. The actual longwave heat transfer may significantly impact thermal comfort depending on the indoor environment. The detailed radiation computation with view factors on idealised individuals is currently explored.

Main References

(max 200 words)

Delpech P., et al. 2005. Pedestrian wind comfort assessment criteria: A comparative Study. EACWE4. Prague: J. Naprestek & C. Fischer.

Nazarian, N., Acero, J. A., & Norford, L. (2019). Outdoor thermal comfort autonomy: Performance metrics for climate-conscious urban design. Building and Environment, 155, 145-160.

Pickup, Janelle, and Richard de Dear. "An outdoor thermal comfort index (OUT_SET*)-part I-the model and its assumptions." Biometeorology and urban climatology at the turn of the millenium. Selected papers from the Conference ICB-ICUC. Vol. 99. 2000.

Subramaniam S. (2017) Daylighting simulations with Radiance using matrix-besed methods, Berkeley Lab, (https://www.radiance-online.org/learning/tutorials/matrix-based-methods)

Edouard Walther, Antoine Hubert, Alexis Sauvageon, Mateusz Bogdan, Improving the Prediction of Natural Ventilation by Coupling CFD and BES : A Case Study in Strasbourg Train Station, IBPSA 2019.

Walther E, Goestchel Q. The PET comfort index: Questioning the model. Building and Environment. 2018 Jun 1;137:1-0.



8:48 - 9:06

Spectral and biological simulation methods for the design of healthy circadian lighting

J. Alstan Jakubiec, Athina Alight

University of Toronto, Canada

Aim and Approach

(max 200 words)

Medical and architectural research has identified that light has significant impacts on alertness, sleep quality, and productivity [1-4]. This has broadly been referred to as circadian lighting, and its effects are dependent on the time of exposure and are sensitive to blue, short wavelength light. Existing calculation methods and standards assess the impact of light on health outcomes [5-7]; however, they have a variety of weaknesses: lacking spectral information, estimating scaling factors to account for spectral power distributions, or relying on instantaneous calculations although light timing and exposure history are crucial in assessing the effects of light on health. No existing methodology calculates spectrally- and temporally-varying light exposure and maps its impact on biological and health-related outcomes. This paper will communicate such a simulation method using time-varying 81-channel spectrally specific lighting simulations [8] and apply the results to existing dynamic photobiology models from medical literature [9]. We predict reaction time, sleepiness, task performance, sleep time and melatonin levels in the bloodstream entirely as a factor of timed light exposure history. This paper shares how these calculation models are implemented, demonstrates them under some week-long scenarios, and proposes new metrics and communication methods to assess the impact of light on health.

Scientific Innovation and Relevance

(max 200 words)

We will present a new scheme for calculating spectral daylight simulations on an annual basis combined with electric lighting which can be dimmed, controlled, and color-shifted on a schedule. Innovations over existing spectral calculation methods include: a physics-based simulation process for the estimation of spatially resolved sky color and spectrum, the inclusion of spectral window and opaque surface materials at a high resolution of 81-channels (5 nm steps) [8], and the calculation of modern non-image forming light quantities following CIE standard S 026 [10]. Furthermore, we present an implementation of a dynamic model of human arousal dynamics [9] which can predict the impact of light on sleep time, subjective sleepiness, task performance, reaction time, and blood plasma melatonin levels. The model is responsive to the time, color, and quantity of light exposure in addition to light history. Two cases are presented using seven days of light history for a modelled occupant. These new calculation methods and metrics will illustrate the actual benefits of lighting design for circadian health, which has not been accomplished using simulation before.

Preliminary Results and Conclusions

(max 200 words)

A new simulation method for time-varying lighting spectra from daylight and controlled electric lighting is presented as well as its application to modelling human circadian biology. Detailed information will be presented on how light interacts with homeostatic and circadian bodily rhythms to impact health and alertness. We calculate the impact of light on sleep time, subjective sleepiness, task performance, reaction time, and blood plasma melatonin levels and present novel methods of evaluating these measures in architectural lighting design. By applying these new models, we present the means to answer longstanding questions regarding the specific health impacts of light exposure in the built environment. Two sample light exposure profiles are calculated over a period of 1 week to illustrate these effects.

In addition to this outcome, a second paper is being prepared to apply our method to a variety of parametric design variants and compare the outcomes to existing methods of evaluating circadian lighting.

Main References

(max 200 words)

1. Rea, M. and M. Figueiro, Light as a circadian stimulus for architectural lighting. Lighting Research & Technology, 2018. 50(4): p. 497-510.

2. Figueiro, M.G., K. Gonzales, and D. Pedler, Designing with circadian stimulus. LD+A: The Magazine of the Illuminating Engineering Society, 2016. 8: p. 30-34.

3. Dijk, D.-J. and S.N. Archer, Light, sleep, and circadian rhythms: together again. PLoS Biol, 2009. 7(6): p. e1000145.

4. Lucas, R.J., et al., Measuring and using light in the melanopsin age. Trends in Neurosciences, 2014. 37(1): p. 1-9.

5. Konis, K., A novel circadian daylight metric for building design and evaluation. Building and Environment, 2017. 113: p. 22-38.

6. Inanici, M., M. Brennan, and E. Clark, Spectral daylighting simulations: Computing circadian light, in Building Simulation. 2015: Hyderabad, India.

7. IWBI, The WELL Building Standard. Washington, DC, Delos Living LLC, 2016.

8. Solemma LLC, ALFA – Adaptive Lighting for Alertness. 2020.

9. Postnova, S., S.W. Lockley, and P.A. Robinson, Prediction of cognitive performance and subjective sleepiness using a model of arousal dynamics. Journal of biological rhythms, 2018. 33(2): p. 203-218.

10. CIE, CIE S 026/E:2018 CIE System for Metrology of Optical Radiation for ipRGC-Influenced Responses to Light. 2018, Commission internationale de l’eclairage.



9:06 - 9:24

An optimization of the switching temperature for an energy system with a double-source heat pump

Sara Bordignon, Giuseppe Emmi, Marco Rossi, Michele De Carli, Angelo Zarrella

Department of Industrial Engineering - Applied Physics Section, University of Padova, Italy

Aim and Approach

(max 200 words)

Enhancing the efficiency of the energy systems for the air-conditioning and domestic hot water production in buildings and reducing the related primary energy consumption through the exploitation of renewable energy sources have become of great interest in the late years.

This paper presents a dynamic analysis of a double-source energy system, aiming at optimally combine the air and the soil as heat source/sink for a heat pump.

In the field of multi-source energy systems, the dual-source heat pump represents a valuable solution to increase the system’s efficiency, compared to a more common air-source heat pump and, at the same time, to reduce the size of the borehole heat exchangers field that should be coupled to a ground source heat pump [1]. These solutions can, therefore, decrease the initial investment and, depending on the plant configurations and on the boundary conditions (i.e. climatic area) [2], an optimisation of the energy system should be carried out to avoid unnecessary oversizing of the components and to further increase the efficiency of the heat pump [3].

Scientific Innovation and Relevance

(max 200 words)

The dynamic energy model is developed in TRNSYS [4] environment, where a novel Type for the modelling of the heat pump is adopted. The purpose of the analysis is to investigate the performances of the system varying the switching temperature, that is the parameter which establishes the heat source to be used by the heat pump. The heat pump Type is a flexible model and can be used as a double-source heat pump. The outputs are based on the polynomials of the compressors, which can be modified by the user, while the fluid properties in the different points of the thermodynamic cycles can be obtained thanks to an internal link to REFPROP [5]. The heat pump is connected to two thermal energy storages from which heat is withdrawn for the air-conditioning and domestic hot water production respectively. Through this approach, it is possible to investigate and predict in detail the thermal and electrical behaviour of double source heat pump systems, which can be used in the context of both retrofitted and new buildings, under different weather conditions.

Preliminary Results and Conclusions

(max 200 words)

The study consisted in the dynamic energy modelling of a double source system where a heat pump exploits both the air and the soil as heat source/sink, for heating, cooling and domestic hot water production of a building. It allows testing a novel TRNSYS Type for the heat pump, which can be used for different simulation applications. The analysis identifies an optimal switching temperature for the investigated case study, which allows increasing the efficiency of the system, reducing the size of the borehole heat exchangers field and decreasing the thermal drift of the ground temperature, due to unbalanced operating condition. The simulations are carried out for different climatic conditions, to make it possible a comparison of the optimal switching temperature for the different locations.

Main References

(max 200 words)

[1] I. Grossi, M. Dongellini, A. Piazzi, and G. L. Morini, “Dynamic modelling and energy performance analysis of an innovative dual-source heat pump system,” Appl. Therm. Eng., vol. 142, pp. 745–759, Sep. 2018.

[2] T. Catalina, J. Virgone, and E. Blanco, “Multi-source energy systems analysis using a multi-criteria decision aid methodology,” Renew. Energy, vol. 36, no. 8, pp. 2245–2252, 2011.

[3] G. Hou, H. Taherian, L. Li, J. Fuse, and L. Moradi, “System performance analysis of a hybrid ground source heat pump with optimal control strategies based on numerical simulations,” Geothermics, vol. 86, p. 101849, Jul. 2020.

[4] University of Wisconsin--Madison. Solar Energy Laboratory. “TRNSYS, a Transient Simulation Program.” Madison, Wis. :The Laboratory, 1975.

[5] M. Lemmon, E.W., Bell, I.H., Huber, M.L., “M.O. NIST Standard Reference Database 23: Reference Fluid Thermodynamic and Transport Properties-REFPROP, Version 10.0.” National Institute of Standards and Technology, Standard Reference Data Program, Gaithersburg, 2018.



9:24 - 9:42

Wind-driven air flow modelling in Modelica: verification and implementation in the IDEAS library

Klaas De Jonge1,3, Filip Jorissen2, Lieve Helsen2,4, Jelle Laverge1

1Ghent University, Department of Architecture and Urban Planning , Belgium; 2University of Leuven (KU Leuven), Department of Mechanical Engineering, Belgium; 3FWO, Research Foundation Flanders; 4EnergyVille, Thor Park, Waterschei, Belgium

Aim and Approach

(max 200 words)

In building simulations, pressure driven airflow and heat flow modelling is often done in separate specialised programs. To include the mutual dependence of indoor temperatures and pressure driven airflow, simulations often require co-simulation using two distinct programs, where CONTAM is often used to compute the system flow rates and pressures. This requires the modeller to be skilled in multiple software packages, and co-simulation. Moreover, the resulting co-simulation framework is hard to extend and customize and an inefficient coupling can cause model inaccuracies or long computation times.

This paper presents a new implementation for pressure driven airflow in the open-source Modelica library IDEAS. It allows the modeller to model the heat transfer and interzonal, pressure driven airflow simultaneously, thereby using one software. This new implementation is validated dynamically by comparing the obtained results with a duplicate of the multi-zone model in the specialised software CONTAM.

Scientific Innovation and Relevance

(max 200 words)

The new implementation will allow modellers to model the mutual dependence of indoor temperatures and pressure driven airflow simultaneously and thus faster. The default implementation does not require extensive additional input which will make it easier for modellers, not familiar with pressure driven airflow, to include this factor. Due to the extensible nature of Modelica, the models can be coupled to detailed HVAC simulations and other system models.

Towards an energy neutral building stock, understanding the different mechanisms at play is key. Combined heating/cooling and ventilation simulations are important to gain a better understanding of the interaction between these depending factors and their impact on energy use and indoor air quality, respectively.

Preliminary Results and Conclusions

(max 200 words)

Results show almost perfect agreement between Modelica IDEAS and CONTAM when zone temperatures are comparable. This shows that the pressure driven airflow implementation is state-of-the-art and may be used as an alternative to co-simulations with CONTAM.

It is important to note that the default integration in IDEAS is limited to predefined airflow elements and relations. This can be a limiting factor for modelling specific airflow paths through a building (e.g. elevator shafts). However, the default implementation can be extended with custom airflow elements to model the additional airflow paths.

Main References

(max 200 words)

[1] F. Jorissen, G. Reynders, R. Baetens, D. Picard, D. Saelens, and L. Helsen, “Implementation and verification of the IDEAS building energy simulation library,” Journal of Building Performance Simulation, vol. 11, no. 6, pp. 669–688, Nov. 2018, doi: 10.1080/19401493.2018.1428361.

[2] W. S. Dols and B. J. Polidoro, “CONTAM User Guide and Program Documentation Version 3.2,” National Institute of Standards and Technology, NIST TN 1887, Sep. 2015. doi: 10.6028/NIST.TN.1887.

[3] M. Wetter, “Multizone Airflow Model in Modelica,” presented at the Modelica 2006, Vienna, Austria, Sep. 2006.



9:42 - 10:00

Evaluation of energy and indoor environmental performance of mechanical ventilation systems under different climatic conditions

Dragos-Ioan Bogatu1, Ongun Berk Kazanci1, Charalampos Angelopoulos2, Daniel Coakley2, Bjarne W. Olesen1

1International Centre for Indoor Environment and Energy, Department of Civil Engineering, Technical 6 University of Denmark, Nils Koppels Allé, Building 402, 2800 Kgs. Lyngby, Denmark; 2Mitsubishi Electric R&D Centre Europe BV, 17 Firth Road (AC3), Houstoun Industrial Estate, Livingston, West Lothian EH54 5DJ

Aim and Approach

(max 200 words)

One of the most significant global development challenges for the built environment is the mitigation of the impact of energy-intensive mechanical heating, ventilation and cooling systems (HVACS) in buildings. Growing population around the world and the fact that people tend to spend almost 90% of their time indoors [1], makes indoor environmental quality an important parameter to account for in new and existing buildings. Nowadays, more people rely on mechanical systems to maintain acceptable levels of Indoor Environmental Quality (IEQ). Mixed-mode buildings combine the use of mechanical and passive techniques to maintain thermally comfortable indoor environments. However, there are no clear guidelines on how to operate such mechanical ventilation systems in order to maintain acceptable levels of IEQ with the minimum possible energy consumption. The aim of this research was to perform dynamic thermal modelling simulations to evaluate the energy and indoor environmental performance of mechanical ventilation systems under different climatic conditions and building types. To examine this, the following objective was used: to identify the optimum operation mode of the mechanical system (bypass, heat recovery or enthalpy recovery) to achieve the energy savings whilst maintaining acceptable levels of IEQ.

Scientific Innovation and Relevance

(max 200 words)

The evaluation of the performance of mechanical systems is often compared to the level of energy use in a building. For the energy use there is one KPI, kWh/m2 per year primary energy, which includes all buildings systems and energy carrier. However, this approach excludes the analysis of parameters for indoor environmental quality such as relative humidity, CO2 concentration, and operative temperature. This paper uses dynamic computer simulations for a residential and an office application to examine the performance of the mechanical ventilation systems under different outdoor conditions and under different indoor heating and cooling loads. The following cases will be analyzed for the climatic conditions of Edinburgh, Scotland; Copenhagen, Denmark; Zurich, Switzerland; and Palermo, Italy: i) Operate ventilation systems in heat recovery mode; ii) Operate ventilation systems in enthalpy recovery mode; and iii) Operate ventilation systems in bypass mode and increased ventilation for cooling (day- and nighttime). In all cases the following KPIs will be used: i) Yearly Room temperature and humidity distribution; ii) Yearly CO2 concentration distribution as an indicator of IEQ; and iii) Energy use of the mechanical systems in the different cases.

Preliminary Results and Conclusions

(max 200 words)

It is expected that the enthalpy recovery mode will have the most effect in very humid and very dry climates. It is predicted that the combination of the passive modes that achieves higher energy savings will depend on the climate, period of the year and building type. It is expected that the enthalpy recovery mode will reach higher energy savings than the heat recovery mode since it allows extracting latent heat from humid air in addition to the recovery of sensible heat. Therefore, it is likely that the outdoor relative humidity and air temperature will influence the amount of energy savings obtained from the enthalpy recovery mode, compared to the heat recovery mode. The bypass mode will probably lead to higher energy savings in periods and locations where the outdoor temperature is lower than the indoor air temperature and there is a need for cooling (e.g. during nighttime in a hot summer period). Finally, it is expected that all the passive strategies analyzed in this study will reach acceptable CO2 concentrations during occupied hours.

Main References

(max 200 words)

[1] N. E. Klepeis, "The National Human Activity Pattern Survey (NHAPS) - A Resource for Assessing Exposure to Environmental Pollutants," Lawrence Berkeley National Laboratory, 2001.

 
8:30 - 10:00Session T1.3: Buildings paving the way for the energy transition
Location: Cityhall (Belfry) - Room 3
Session Chair: Wilfried GJHM van Sark, Utrecht University
Session Chair: Javier Arroyo, KU Leuven
Cityhall (Belfry) - Room 3 
 
8:30 - 8:48

PCM-enhanced building envelope for improved thermal comfort and energy efficiency in danish buildings

Morten Hagenau, Muhyiddine Jradi

University of Southern Denmark, Denmark

Aim and Approach

(max 200 words)

The building sector accounts for 40% of the Danish energy consumption profile with an equivalent share in the emission of greenhouse gasses [1]. With this large contribution, increasing the efficiency of this sector is key for reaching future energy goals. Considering the Danish building regulations [2], it can be noted that the requirements for new buildings have increased drastically, both on the level of the building envelope and the quality and specifications of energy systems. Alongside active energy improvements dealing with energy supply systems [3], passive techniques targeting the building envelope are demonstrated as viable options to improve the building performance [4]. In this study, a holistic investigation of integrating phase change materials within the building envelope is presented aiming to improve indoor thermal comfort and reduce energy consumption. A dynamic energy modeling and performance evaluation of building envelope enhanced with phase change materials under Danish conditions is carried out. Three case study real buildings are considered, where corresponding holistic dynamic energy models are developed and calibrated using actual collected data. Using the calibrated energy models, the impact of a PCM-enhanced building envelope in the three cases is simulated and evaluated on both thermal comfort and energy consumption.

Scientific Innovation and Relevance

(max 200 words)

A large block of studies has investigated PCM applications in buildings from different perspectives, divided as active and passive applications [5]. Active PCM applications are PCM modules integrated within the building HVAC system as an active energy storage component. On the other hand, passive applications take the form of PCM-enhanced building envelope, where the PCM is embedded within the envelope constructions as an interdependent layer or mixed with another material. Nevertheless, the PCM potential in storing latent heat has proven to be one of the drivers of net zero energy building design [6]. The recent investigations have clearly shown the large potential of PCM-enhanced building envelope applications in reducing the overall cooling and heating load and hence the corresponding greenhouse gas emissions. As the danish building regulation is being progressively tightened concerning the building envelope and the overall energy performance of buildings, PCM integration in the building component provide a potential alternative to enhance the overall thermal envelope and reduce heating and cooling loads. In this context, the impact of using PCMs within building envelopes on the heating and cooling energy consumption of Danish buildings has not been extensively studied, in particular through using dynamic energy modeling and simulations.

Preliminary Results and Conclusions

(max 200 words)

The evaluation of the impacts of implementing PCMs within the building envelope is carried out by employing dynamic energy models. As the PCM charging and discharging is a dynamic process affected by multiple factors, the use of such models is key towards a more accurate prediction of the PCM behavior. Three case study buildings are considered, a university office building, a daycare center and a residential single-family house. Using EnergyPlus, dynamic energy models are developed and calibrated using actual data. Then, the calibrated models were employed to simulate and evaluate the impact of a PCM-enhanced building envelope on both thermal comfort and energy consumption. The results demonstrate a reduction on energy consumption ranging from 5 to 33%, with a reduction in the peak summer temperature of up to 5°C. The results of this work will serve as a basis for passive PCM applications in Danish buildings and will aid the use of PCM-enhanced envelope in the design of future energy efficient and Danish net zero energy buildings. This is supported by the reported considerable energy consumption reduction, cooling, and heating loads reduction as well as the decrease in the average indoor temperature in the summer in the three buildings investigated.

Main References

(max 200 words)

[1] Jradi, M., Veje, C., Jørgensen, B.N. (2017): Deep energy renovation of the Mærsk office building in denmark using a holistic design approach. Energy and Buildings 151, 306-319.

[2] Bygningsreglementet, The Danish Building Regulations (2020). https://bygningsreglementet.dk/

[3] Derradji, L., Errebai, F.B., M. Amara, M. (2017): Effect of PCM in improving the thermal comfort in buildings. Energy Procedia 107, 157-161.

[4] Rathore, P.K.S., Shukla, S.K. (2019): Potential of macroencapsulated PCM for thermal energy storage in buildings: a comprehensive review. Construction and Building Materials 225, 723-744.

[5] Iten, M., Liu, S., Shukla, A. (2016): A review on the air-PCM-TES application for free cooling and heating in the buildings. Renewable and Sustainable Energy Reviews 61, 175-186.

[6] Kenzhekhanov, S., Memon, S.A., Adilkhanova I. (2020): Quantitative evaluation of thermal performance and energy saving potential of the building integrated with PCM in a subarctic climate. Energy 192, 116607.



8:48 - 9:06

Comparison of data-driven model-based and model-free control approaches for unlocking building energy flexibility

Anjukan Kathirgamanathan1,3, Eleni Mangina2,3, Donal P. Finn1,3

1School of Mechanical and Materials Engineering, University College Dublin, Ireland; 2School of Computer Science, University College Dublin, Ireland; 3Energy Institute, University College Dublin, Ireland

Aim and Approach

(max 200 words)

Utilisation of energy flexibility in buildings, within a demand side management context, is increasingly being considered as a vital contributor to the future smart grid [1]. However, due to the heterogenous nature of the building stock, developing computationally tractable control-oriented models, which adequately represent the complex and nonlinear thermal-dynamics of individual buildings, is proving to be a major hurdle [2]. The current paper compares two predictive control techniques to harness energy flexibility in buildings; using a data-driven model-based approach and a model-free approach. The ‘separation of variables’ technique together with the random forest algorithm is tested as the model-based approach [3]. A ‘Soft Actor Critic’ reinforcement learning agent is used as the model-free approach.

A white-box EnergyPlus model of an archetype commercial building is used as the virtual testbed building for designing and evaluating the two control approaches. Energy flexibility is provided through the use of building passive thermal mass, active thermal energy storage, on-site photovoltaic generation, and electrical battery storage. Both control approaches are evaluated for ease of design, computational burden and efficacy of the control performance to utilise the energy flexibility on the basis of dynamic signals from the grid.

Scientific Innovation and Relevance

(max 200 words)

Data-driven approaches show promising potential in unlocking energy flexibility in commercial buildings where the cost of deriving a first-principles physics based model is high or in some cases impracticable [4]. With commercial buildings being complex and exhibiting non-linear behaviour, building control based on physics based models has often been limited to being rudimentary and non-predictive and hence unable to fully harness the energy flexibility such buildings possess. A literature review of prior work, on the application of data-driven methods for building demand side management, has shown that two distinct data-driven control approaches exist: model-based and model-free [2]. To the best knowledge of the authors, there have been limited comparisons made of the two approaches on a benchmark case. Without such benchmarks, it is very difficult to compare the efficacy and scalability of the different techniques due to the varying buildings and dynamic boundary conditions used in individual studies [2]. The current research, which is being carried out as part of the IEA Annex 81 Data-Driven Smart Buildings [5], will aid in understanding the relative benefits and challenges of both control approaches as applied to an archetype building.

Preliminary Results and Conclusions

(max 200 words)

A 12 storey, 46,000 m2 floor area, commercial office building was used as a case study. The model-based controller was developed using Python, with the Eppy package and an OPC bridge used for co-simulation together with EnergyPlus. In the model-free case, the Gym-Eplus package was used as a wrapper for the OpenAI gym environment and to interface with EnergyPlus. Preliminary work has applied the model-based approach (separation of variables using random forests) in the optimal control of the building under dynamic pricing signals and found that the controller is able to shift consumption thereby reducing the energy cost to the building. Separately, the model-free approach, using the ‘Soft Actor Critic’ reinforcement learning algorithm, has been applied to different buildings as part of the CityLearn competition [6]. The reinforcement learning technique was shown to be capable of smoothening the district demand profile. Ongoing work aims to apply both techniques to the same virtual testbed building and benchmark the performance of the controllers. This work is essential in aiding the widespread adoption of data-driven control approaches to the building demand side management problem.

Main References

(max 200 words)

[1] K. O. Aduda, T. Labeodan, W. Zeiler, G. Boxem, and Y. Zhao, “Demand side flexibility: Potentials and building performance implications,” Sustain. Cities Soc., vol. 22, pp. 146–163, 2016.

[2] A. Kathirgamanathan, M. De Rosa, E. Mangina, and D. P. Finn, “Data-driven Predictive Control for Unlocking Building Energy Flexibility: A Review,” Renew. Sustain. Energy Rev., vol. In Press., 2020.

[3] A. Jain, F. Smarra, and R. Mangharam, “Data Predictive Control using Regression Trees and Ensemble Learning,” 2017 56th IEEE Conf. Decis. Control, vol. 135, pp. 4446–4451, 2017.

[4] F. Smarra, A. Jain, T. De Rubeis, D. Ambrosini, A. D. Innocenzo, and R. Mangharam, “Data-driven model predictive control using random forests for building energy optimization and climate control,” Appl. Energy, vol. 226, pp. 1252–1272, 2018.

[5] IEA EBC Annex 81, “Data-Driven Smart Buildings EBC ANNEX 81,” 2019.

[6] J. R. Vázquez-Canteli, J. Kämpf, G. Henze, and Z. Nagy, “CityLearn v1.0: An OpenAI gym environment for demand response with deep reinforcement learning,” BuildSys 2019 - Proc. 6th ACM Int. Conf. Syst. Energy-Efficient Build. Cities, Transp., pp. 356–357, 2019.



9:06 - 9:24

Time-based economic hierarchical model predictive control of all-electric energy systems in non-residential buildings

Laura Maier, Larissa Kühn, Philipp Mehrfeld, Dirk Müller

RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate

Aim and Approach

(max 200 words)

Model predictive control (MPC) is a known approach to optimize building energy system (BES) operation. In this context, studies prove that the choice of control and prediction horizons are dependent on the regarded BES and its boundary conditions. In some cases, a mix of large and short prediction horizons is useful to exploit the BES´s full potential. This is especially true for seasonal storages or for economic boundary conditions, based on a long-term performance. This challenge is met by the concept of hierarchical MPC (HMPC). HMPC separates the control problem in different layers. In literature, these layers can be time-based and/or space-based. In this work, we focus on a time-based approach in order to incorporate seasonal pricing effects.

This work aims at assessing the potential of time-based HMPC based on mixed integer linear and quadratic programs (MILP and MIQP) from an eco-economic point of view. The use case is a non-residential BES basing on electricity only. The BES consists of two types of storages (battery, electric vehicles) and local electricity generation by photovoltaics (PV). We couple a MILP- and MIQP-based HMPC with a dynamic simulation using validated Modelica models to evaluate the BES´s operation under predefined eco-economic scenarios.

Scientific Innovation and Relevance

(max 200 words)

In scientific literature, different MPC approaches for the optimization of BES operation have already been investigated. However, for the combination of PV, battery and electric vehicles, the main focus lies on residential buildings. Here, we focus on non-residential buildings by applying the deduced methodology to a business and innovation center in Berlin called FUBIC. FUBIC is a highly complex, interconnected BES. The simultaneous occurrence of heating and cooling demands as well as the integration of components whose efficiency depends on the boundary condition represent an additional challenge for the HMPC.

We contribute to research in this field by optimizing FUBIC´s operation with regard to defined eco-economic scenarios. We evaluate the suitability of a MILP and MIQP approach for time-based HMPC. Furthermore, we compare the HMPC to a conventional rule-based control concept and to a 1-layer MPC approach. Thus, we can assess the potential of a time-based HMPC concept. Based on this, we deduce factors, which support the use of time-based HMPC structures.

Preliminary Results and Conclusions

(max 200 words)

Preliminary results indicate that the HMPC leads to lower operating costs and CO2 emissions in comparison to a 1-layer MPC approach and the conventional rule-based control.

However, we detect a gap in the large and short prediction horizon optimization. The large prediction horizon optimization differs greatly from the short one in some periods. This is caused by model simplifications in the upper layer on the one hand and the constraints, which are communicated between the layers, on the other hand. Consequently, for the proper implementation of a time-based HMPC, it is important to assess how and which constraints are communicated between the layers.

Apart from that, the economic boundary conditions and the storage size influence the value added by a time-based HMPC structure the most. Moreover, it becomes obvious that the 1-layer approach also results in lower operating costs and CO2 emissions compared to the rule-based control concept but the whole potential of MPC control is not exploited.

Main References

(max 200 words)

S. Kim, J. Kim, K. Cho and G. Byeon, "Optimal Operation Control for Multiple BESSs of a Large-Scale Customer Under Time-Based Pricing," in IEEE Transactions on Power Systems, vol. 33, no. 1, pp. 803-816, Jan. 2018, doi: 10.1109/TPWRS.2017.2696571.

R. Kumar, M. J. Wenzel, M. J. Ellis, M. N. ElBsat, K. H. Drees and V. M. Zavala, "Handling Long Horizons in MPC: A Stochastic Programming Approach," 2018 Annual American Control Conference (ACC), Milwaukee, WI, 2018, pp. 715-720, doi: 10.23919/ACC.2018.8430780.

M. E. Raoufat, B. Asghari and R. Sharma, "Model predictive BESS control for demand charge management and PV-utilization improvement," 2018 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, 2018, pp. 1-5, doi: 10.1109/ISGT.2018.8403403.

Y. Shi, B. Xu, D. Wang and B. Zhang, "Using Battery Storage for Peak Shaving and Frequency Regulation: Joint Optimization for Superlinear Gains," 2018 IEEE Power & Energy Society General Meeting (PESGM), Portland, OR, 2018, pp. 1-1, doi: 10.1109/PESGM.2018.8586227.

K. Vatanparvar and R. Sharma, "Battery Optimal Approach to Demand Charge Reduction in Behind-The-Meter Energy Management Systems," 2018 IEEE Power & Energy Society General Meeting (PESGM), Portland, OR, 2018, pp. 1-5, doi: 10.1109/PESGM.2018.8586597.



Large-scale multicriteria sorting for the integration of photovoltaic systems in the urban environment

Martin Thebault1, Gilles Desthieux2, Christophe Ménézo1

1University Savoie Mont Blanc, LOCIE/FRESBE, F- 74944 Annecy-le-Vieux, France; 2Haute école du paysage d’ingénierie et d’architecture de Genève (hepia), Institute for Landscaping Architecture Construction and Territory (inPACT), University of Applied Sciences Western Switzerland, Geneva, Switzerland

Aim and Approach

(max 200 words)

This work proposes a multicriteria approach in order to evaluate the suitability of a building to be equipped with Photovoltaic (PV) systems. In the present case, technical (roofs complexity), economic (payback period), environmental (CO2 reduction), energetic (self-consumption) as well as social (heritage constraints) are considered. These criteria are evaluated for each building of the Great Geneva agglomeration, then a multicriteria methods, ELECTRE TRI, allows to sort these roof in three categories that corresponds to “Very High”, “High”, “Moderate” suitability.

Scientific Innovation and Relevance

(max 200 words)

Sorting processes have been widely used in cities. They take the form of GIS tools called solar cadastres (IRENA, 2019). The solar cadastre of a city is a geographical interface, which makes it possible to know how much sunlight a given roof, building, home or a part of them receives. In most of the current cadastres, roofs are sorted based on the solar irradiation they receive i.e. the energy received yearly per square meter.

However, cities are complex environments and information about the solar potential is not sufficient when assessing the suitability of a roof to host a photovoltaic systems. Other key aspects must be considered such as, for instance, the presence of superstructure elements on the roof (Desthieux 2018), structural robustness, economic feasibility (Sommerfeldt 2017) or the heritage and aesthetic character of the given building (Florio 2018). Therefore, the sortings that have been proposed are limited as they do not address the multicriteria aspect of the suitability of a roof to host PV systems.

Preliminary Results and Conclusions

(max 200 words)

This paper presents a sorting methodology of the buildings according to their suitability to be equipped with PV systems. This sorting is based on a multicriteria approach performed using the ELECTRE TRI method. The different criteria considered are, the self-sufficiency, the payback periods, the roof complexity, the reduction in CO2 emissions and the heritage constraints. Three classes of suitability are defined which are ‘Very high’, ‘High’ and ‘Moderate’ suitability.

The method is then applied to the case of the Geneva Agglomeration (Grand Genève). This French-Swiss region is composed of nearly 260000 buildings. The different parameters of the ELECTRE TRI models are defined based on discussion with experts (thresholds, weights, limits of the classes, …).

The methodology successfully allows to evaluate the suitability of the roofs and provide a relevant tool to help decision makers into identifying the right building for PV system installation.

Main References

(max 200 words)

IRENA, 2019. Solar simulators: Application to developing cities [WWW Document]. Publ.-SimulatorsAppl.--Dev.-Cities. URL /publications/2019/Jan/Solar-simulators-Application-to-developing-cities (accessed 10.17.19).

Desthieux, G., Carneiro, C., Camponovo, R., Ineichen, P., Morello, E., Boulmier, A., Abdennadher, N., Dervey, S., Ellert, C., 2018. Solar Energy Potential Assessment on Rooftops and Facades in Large Built Environments Based on LiDAR Data, Image Processing, and Cloud Computing. Methodological Background, Application, and Validation in Geneva (Solar Cadaster). Front. Built Environ. 4. https://doi.org/10.3389/fbuil.2018.00014

Thebault, Martin, Vincent Clivillé, Lamia Berrah, et Gilles Desthieux. 2020. « Multicriteria roof sorting for the integration of photovoltaic systems in urban environments ». Sustainable Cities and Society, 102259.

Figueira, J., Greco, S., Ehrgott, M., 2005. Multiple criteria decision analysis: state of the art surveys. Springer Science & Business Media.

 
8:30 - 10:00Session T1.4: Improving indoor environmental quality
Location: Cityhall (Belfry) - Room 4
Session Chair: Dariusz Heim, Lodz University of Technology
Session Chair: Hayder Alsaad, Bauhaus-University Weimar
Cityhall (Belfry) - Room 4 
 
8:30 - 8:48

Development of a 3D and high resolution dynamic thermal model of a room with sun patch evolution for thermal comfort applications

Teddy Gresse1, Lucie Merlier2, Jean-Jacques Roux1, Frédéric Kuznik1

1Univ Lyon, INSA Lyon, CNRS, CETHIL, UMR5008, 69621 Villeurbanne, France; 2Univ Lyon, UCBL, INSA Lyon, CNRS, CETHIL, UMR5008, 69622 Villeurbanne, France

Aim and Approach

(max 200 words)

Rapidly varying environmental phenomena, such as solar radiation or airflows can significantly affect thermal comfort. Hence, this contribution presents the development and validation of an efficient dynamic thermal model designed to simulate a room for thermal comfort applications, using a 3D and high-resolution description of heat conduction in the envelope and surface balances. In particular, the model can handle short-time steps and calculates the sun patch, which corresponds to the projection of solar radiation through a window onto interior walls.

The model is validated using detailed experimental data of a low energy building called BestLab [1]. Surface temperature and indoor air temperature are especially compared, and the discrepancies are quantified.

Scientific Innovation and Relevance

(max 200 words)

Building thermal models generally aim to predict the energy consumption of buildings. Thus, they consider thermal loads over a long period such as a year, and neglect or simplify some features of thermal transfers. Conduction in the building envelope is typically considered 1D, short-wave radiation is projected on the floor and typical hourly weather data are used.

Yet, buildings and indoor environmental conditions are exposed to rapid environmental variations. As a response, surface temperature distribution, indoor airflows and room air temperature may substantially but locally vary, which can affect the thermal comfort of inhabitants [2] [3]. Thus, relevantly addressing thermal comfort requires higher resolution simulations able to manage locally rapid environmental variations. In particular, the use of a 3D model that includes the calculation of the sun patch and relevant convective effects can significantly improve thermal comfort prediction thanks to a better prediction of the different indoor environmental quantities [4] [5].

Preliminary Results and Conclusions

(max 200 words)

The developed model is already able to simulate the three-dimensional heat conduction in a typical cubic room with a refined mesh. The sun patch detection is also successfully implemented.

Regarding the reference validation case, the complex geometry and mesh of the test case are well reproduced. To complete this validation study, current developments focus on the implementation of varying boundary conditions using weather data that vary over short time-steps.

Next step is to couple this thermal model with Computational Fluid Dynamics (CFD) to improve the description of indoor convective transfers at the walls and obtain an accurate and detailed operative temperature map for thermal comfort prediction.

Main References

(max 200 words)

[1] A. Rodler, "Modélisation dynamique tridimensionnelle avec tache solaire pour la simulation du comportement thermique d'un batiment basse consommation," 2014.

[2] E. Arens, H. Zhang and C. Huizenga, "Partial- and whole-body thermal sensation and comfort—Part II: Non-uniform environmental conditions," Journal of Thermal Biology, 2006.

[3] Y. Zhang and R. Zhao, "Relationship between thermal sensation and comfort in non-uniform and dynamic environments," Building and Environment, 2009.

[4] A. Rolder, J. Virgone and J.-J. Roux, "Sun patch impact for the evaluation of operative temperatures distributions," Engineering and Architecture (SCEA), 2014.

[5] A. Rodler, J.-J. Roux, J. Virgone, K. Eui-Jong and J.-L. Hubert, "Are 3D heat tranfer formulations with short time-step and sun patch evolution necessary for building simulation?," Conference paper, 2013.



8:48 - 9:06

Impact of building thermal inertia in different climates using energy dynamic simulation through a simplified description model

Roberto Rugani1, Marco Bigazzi1, Fabio Fantozzi1, Marco Marengo2, Marco Picco2, Giacomo Salvadori1

1University of Pisa, Pisa, Italy; 2University of Brighton, Brighton, United Kingdom

Aim and Approach

(max 200 words)

This study is part of a wider research aimed at creating building type databases for simplified dynamic thermal models of buildings. Among all the factors that influence energy consumption and comfort, the control of internal temperature is undoubtedly the crucial issue [1][2]. The environment temperature variations caused by all the heat exchanges mainly depend on several parameters related to the way the building is designed [3]: the thermal-physical properties of the building materials are surely the main parameters. For many years the quality of building envelopes has been assessed only on the reduction of thermal transmittance [4]; however, recent researches have shown that, especially in order to reduce the need for cooling energy, not only thermal transmittance but also heat capacity should be carefully considered [5]. Thermal inertia causes temporal variations in the heat transfer of external conditions inside the building, and vice versa; although standards such as EN-ISO-13786 allow its impact to be evaluated using semi-stationary methods, the only way to correctly understand its effect is to use dynamic tools. The aim of this project is to evaluate the thermal inertia of the building envelope under different weather conditions, using a simplified dynamic building energy simulation screening tool [6].

Scientific Innovation and Relevance

(max 200 words)

Several building envelopes have been conceived and compared in order to analyse the impact of thermal inertia. Therefore, a database regarding envelope’s constructions and transparent surfaces has been developed to be exhaustive, flexible and modular. This database has then been implemented in a simplified dynamic simulation tool that has been used to evaluate the impact of thermal inertia of different building solutions in the internal comfort of an edifice and in its energy consumption. The tool is based on the well-known building performance simulation program EnergyPlus; and the associated simplified model used has been defined in previous studies by assessing the impact of simplifications on simulation results [7].

The goal of this study is to evaluate the behaviour of different envelopes in two significantly different climate conditions representative of the European climate (London and Brindisi) and for two end uses: residential and office. In order to do so, four comparisons have been identified: envelope with similar transmittance values, but different areal heat capacity; different insulation position in heavyweight envelopes; envelope with similar periodic transmittance values, but different internal heat capacity; and the impact of using PCM boards in lightweight envelopes.

Preliminary Results and Conclusions

(max 200 words)

In order to compare the results of the dynamic energy simulations, a standard building have been defined at geometric level, conceived as a parallelepiped.

Comparisons are based on both thermal comfort and consumption. In particular, in order to evaluate the occupants' internal comfort, operative temperature has been chosen as a suitable parameter (EN-ISO-15251)[8].

From the results can be concluded that thermal inertia has a great relevance, especially in warm climates where energy savings achieved up to 8%. The important role of the internal heat capacity is highlighted by the results of the second and third comparisons, in which, assuming the same periodic transmittance, the envelope with the highest heat capacity has 12% less discomfort levels and 5% less cooling need than the others. In addition, a passive strategy such as a good night-time ventilation during summer has a much more positive impact on high-inertia envelopes, with energy savings up to 17%. However, lightweight envelopes have several advantages, ensuring an adequate level of transmittance with lower thicknesses. Therefore, the analysis has been extended to PCM boards as a solution to improve the dynamic behaviour of lightweight structures, with a tested result of only 1% higher cooling need than the heavyweight envelope.

Main References

(max 200 words)

1. European Parliament Directive 2010/31/EU on the energy performance of buildings. Off. J. Eur. Union 2010.

2. European Parliament Directive (EU) 2018/844 amending Directive 2010/31/EU on the energy performance of buildings and Directive 2012/27/EU on energy efficiency. Off. J. Eur. Union 2018.

3. Pacheco, R.; Ordóñez, J.; Martínez, G. Energy efficient design of building: A review. Renew. Sustain. Energy Rev. 2012, 16, 3559–3573, doi:10.1016/j.rser.2012.03.045.

4. Stazi, F. Thermal Inertia in Energy Efficient Building Envelopes; Stazi, F.B.T.-T.I. in E.E.B.E., Ed.; Butterworth-Heinemann, 2017; ISBN 978-0-12-813970-7.

5. Leccese, F.; Salvadori, G.; Asdrubali, F.; Gori, P. Passive thermal behaviour of buildings: Performance of external multi-layered walls and influence of internal walls. Appl. Energy 2018, 225, 1078–1089, doi:10.1016/j.apenergy.2018.05.090.

6. Picco, M.; Marengo, M. A Fast Response Performance Simulation Screening Tool in Support Of Early Stage Building Design. Proc. 16th IBPSA Conf. 2019, 1296–1303, doi:10.26868/25222708.2019.210252.

7. Picco, M.; Marengo, M. Energy simulation in early stage building design: Simplified models and impact on results. Build. Simul. Appl. 2015, 2015-February, 119–126.

8. EN 15251:2007 Indoor environmental input parameters for design and assessment of energy performance of buildings addressing indoor air quality, thermal environment, lighting and acoustics; 2007;



9:06 - 9:24

Bedroom environmental discomforts, occupant behaviors, and sleep quality based on an online survey

Chenxi Liao1,2, Jelle Laverge1, Mizuho Akimoto3, Chandra Sekhar4, Pawel Wargocki2

1Research group Building Physics, Construction and Climate Control, Department of Architecture and Urban Planning, Ghent University, Belgium; 2International Centre for Indoor Environment and Energy, Department of Civil Engineering, Technical University of Denmark; 3Department of Architecture, Waseda University; 4School of Design and Environment, National University of Singapore

Aim and Approach

(max 200 words)

The purpose of this study was to examine the association between discomfort in bedrooms caused by noise, stuffy air, “too warm”, “too cool” conditions, and sleep quality, and the association between occupant behaviors and environmental discomfort in bedrooms, as well as the association between occupant behaviors and sleep quality. An online questionnaire survey was conducted in the summer to investigate the sleep quality of people living in Belgium (temperate climate). It investigated the level of discomfort, if any, and sleep quality. Last but not least, the situation of bedroom environmental discomforts can be used for defining indoor environmental quality in building simulation.

Scientific Innovation and Relevance

(max 200 words)

Bedroom comfort affects sleep quality, which is vital for humans health and next-day performance (Hirshkowitz et al., 2015; Opp, 2009). An increasing number of studies showed the importance of thermal comfort (Imagawa and Rijal, 2015; Lee and Shaman, 2017; Lei et al., 2017), air quality (Laverge and Janssens, 2012; Mishra et al., 2018; Strom-Tejsen et al., 2016), and acoustic comfort (Caddick et al., 2018) for good sleep quality. However, previous studies mainly focused on the effect of only one factor of bedroom environment on sleep quality, although thermal comfort, air quality, and acoustic comfort may influence sleep quality interactively, where at least for thermal comfort and indoor air quality (Xiong et al., 2020). In this study, the frequencies of bedroom environmental discomforts of “too warm”, too cool”, noise and stuffy air, sleep quality (the Pittsburgh Sleep Quality Index (PSQI)), as well as occupant behaviors, were investigated, via an online questionnaire survey in Belgium (temperate climate), from July to August 2020.

Preliminary Results and Conclusions

(max 200 words)

A total of 83 responses was received. The respondents were 43 males and 40 females aged 27 – 32 years. Almost half of the respondents (47.7 %) had a PSQI score greater than 5, which was indicated as poor sleepers. A total of 87.8%, 68.9%, 32.4% and 18.9% of respondents were disturbed regularly or occasionally during sleep by “too warm” conditions, noise, stuffy air and “too cool” conditions, respectively. Responses of people who were disturbed by “too warm” conditions were significantly associated with poor sleep quality; 67.4% of PSQI scores were higher compared to those who were not disturbed (p < 0.05). The PSQI scores increased with the increasing number of bedroom environmental discomforts, the effect being close to significance (p-trend < 0.066). It was concluded that “too warm” conditions were the major bedroom environmental discomfort in summer in Belgium. People experienced poor sleep quality if they were disturbed by more than one of the bedroom environmental discomforts. This study investigated to what extent were people disturbed by thermal discomfort, noise and stuffy air during sleep in summer. More similar studies are required to be conducted in the other three seasons or regions.

Main References

(max 200 words)

Caddick, Z. A., et al., 2018. A review of the environmental parameters necessary for an optimal sleep environment. Building and Environment. 132, 11-20.

Hirshkowitz, M., et al., 2015. National Sleep Foundation's sleep time duration recommendations: methodology and results summary. Sleep Health. 1, 40-43.

Imagawa, H., Rijal, H. B., 2015. Field survey of the thermal comfort, quality of sleep and typical occupant behaviour in the bedrooms of Japanese houses during the hot and humid season. Architectural Science Review. 58, 11-23.

Laverge J., Janssens A., 2012. Analysis of the influence of ventilation rate on sleep pattern. Indoor Air Conferences. Austin, TX: ISIAQ.

Lee, W. V., Shaman, J., 2017. Heat-coping strategies and bedroom thermal satisfaction in New York City. Science of the Total Environment. 574, 1217-1231.

Lei, Z. P., et al., 2017. Effect of natural ventilation on indoor air quality and thermal comfort in dormitory during winter. Building and Environment. 125, 240-247.

Mishra, A. K., et al., 2018. Window/door opening-mediated bedroom ventilation and its impact on sleep quality of healthy, young adults. Indoor Air. 28, 339-351.

Opp, M. R., 2009. Sleeping to fuel the immune system: mammalian sleep and resistance to parasites. Bmc Evolutionary Biology. 9.

...



9:24 - 9:42

Phase-change materials selection: numerical study based on design of experiments.

Gilles Baudoin, Geoffrey van Moeseke

Université catholique de Louvain, UCLouvain, Belgium

Aim and Approach

(max 200 words)

Researchers have shown an increased interest in phase-change materials (PCM) to modify thermal mass in buildings. PCM offer an opportunity to increase the thermal mass effect on a given temperature range. A key aspect of PCM selection is the melting temperature but the optimised melting temperature may significantly vary in the literature.

The melting temperature selection could be affected by the properties of the PCM-enhanced component, by the climate and by the building under investigation. To the best of our knowledge, the influence of the building under investigation has never been systematically studied. Therefore, this study aims to quantify the influence of the building parameters on the PCM selection, and more specifically on the optimal melting temperature.

Dynamic simulations of a test-cell in a temperate climate are currently being conducted with EnergyPlus. Various combinations of the building parameters were selected based on design of experiments. For each combination, a case with and without PCM were compared to determine the potential gains of using PCM on energy needs, both for cooling ΔEcool and heating ΔEheat. A metamodel was then constructed to link the energy savings ΔEcool and ΔEheat., with the building parameters in the form of a second order polynomial function.

Scientific Innovation and Relevance

(max 200 words)

To our knowledge, it is the first time that optimal melting temperature is systematically studied for different building parameters. While previous studies were focusing on specific cases, this investigation will allow to generalise the results to a larger set of building configurations.

Knowing the effect of the building parameters on the PCM selection would also allow (i) to facilitate PCM selection in early design phase and (ii) to evaluate the impact of operational conditions on PCM selection. Moreover, this study will provide some support for the original idea of using two different melting temperatures to optimise thermal mass in the building sector. It would allow to identify the best PCM for heating and the one for cooling. In further investigations, combinations of these two PCMs could be compared with the addition of one PCM only.

Preliminary Results and Conclusions

(max 200 words)

Initial results were obtained with eight different building parameters, e.g. wall insulation, and three different PCM-panels. They indicated that: (i) the achievable savings could be higher for cooling than for heating and (ii) an inadequate melting temperature selection could even lead to negative effect for heating. However, these results were not sufficient to identify the different influences of each building parameter on the PCM selection.

The next step is to add the melting temperature in the metamodel. The solution being investigated is to calculate the optimised melting temperature for each combination of parameters, and to build a metamodel for the optimised melting temperature. This metamodel would directly link the optimised melting temperature with the building parameters.

Main References

(max 200 words)

S. E. Kalnæs, B. P. Jelle, Phase change materials and products for building applications: A state-of-the-art review and future research opportunities, Energy and Buildings 94 (2015) 150–176.

P. C. Tabares-Velasco, C. Christensen, M. Bianchi, Verification and validation of EnergyPlus phase change material model for opaque wall assemblies, Building and Environment 54 (2012) 186–196.

M. Saffari, A. de Gracia, S. Ushak, L. F. Cabeza, Economic impact of integrating PCM as passive system in buildings using Fanger comfort model, Energy and Buildings 112 (2016) 159–172.

G. Evola, L. Marletta, F. Sicurella, A methodology for investigating the effectiveness of PCM wallboards for summer thermal comfort in buildings, Building and Environment 59 (2013) 517-527.

M. Mäkelä, Experimental design and response surface methodology in energy applications: A tutorial review, Energy Conversion and Management 151 (2017) 630–640.

S.-G. Yong, J. Kim, J. Cho, J. Koo, Meta-models for building energy loads at an arbitrary location, Journal of Building Engineering 25 (2019) 100823.

P. Westermann, R. Evins, Surrogate modelling for sustainable building design – A review, Energy and Buildings 198 (2019) 170–186.



9:42 - 10:00

Study of the influence of temperature on the moisture buffering capacity of bio-based concretes

Igue Fathia Dahir1, Anh Dung Tran Le1, Alexandra Bourdot2, Promis Geoffrey1, Sy Tuan Nguyen3, Omar Douzane1, Laurent Lahoche1, Thierry Langlet1

1University of Picardie Jules Verne, France; 2Ecole normale supérieure Paris-Saclay, France; 3University of Science and Technology – the University of Danang, Viet Nam

Aim and Approach

(max 200 words)

The aim of this article is investigate the hygric performances of bio-based materials. The MBV value characterizes the ability of a material or multi-layer component to moderate the variation of indoor relative humidity (RH). In the literature, the moisture buffer value was determined at a constant temperature, normally at 23°C. However, in reality, the indoor temperature of the buildings is variable. Therefore, this study will examine the influence of temperature on the moisture buffer value (MBV). First, the physical models are presented. Second, the numerical models have been implemented in the Simulation Problem Analysis and Research Kernel (SPARK) suite to the complex problems. Then, the simulation tools are validated with the experimental results found in the literature. The study will be carried out on a building envelope made of palm and sunflower concretes (bio-based concretes). The boundary conditions of the studied wall are chosen according to the protocol proposed in the NordTest to calculate MBV value as function of temperature. The results showed that the increase in temperature induces an increase in the MBV value. Using this numerical model presented in this paper can predict and optimize the hygric performance of bio-based materials designed for building application.

Scientific Innovation and Relevance

(max 200 words)

Bio-based concretes (such as hemp concrete, flax concrete…) are dedicated to natural construction which is a mean of achieving sustainable construction over time.

In the literature, the moisture buffer value (MBV) was determined at constant temperature, 23°C. However, in reality, the indoor temperature of the buildings is variable. The experimental results showed that the MBV value is impacted by the temperature. For example, MBV values of palm concrete measured at 23°C and 10°C are 2.96 and 2.03 (g.m-2. % RH-1) respectively (with a percentage deviation of 31.42 %). Therefore, it is necessary to carry out an in-depth study on the impact of temperature on the MBV value of bio-based materials.

The use of the presented numerical model which has been validated experimentally can predict and optimize the hygric performance of bio-based materials designed for building application.

Preliminary Results and Conclusions

(max 200 words)

The numerical model to study the influence of temperature on the MBV value has been validated by comparing with the results found in the literature.

The preliminary results showed that the increase in temperature induces an increase in the MBV value and using the numerical model presented in this paper can predict and optimize the hygric performance of bio-based materials.

Main References

(max 200 words)

Chennouf, N., Agoudil, B. 2018. « Hygrothermal characterization of a new bio-based construction material: Concrete reinforced with date palm fibers ». Construction and Building Materials (192): 382-394. doi.org/10.1016/j.conbuildmat.2018.10.089.

Janssen, H., Roels, S. 2009. « Qualitative and quantitative assessment of interior moisture buffering by enclosures ». Energy and Building 41 (4): 382-394. doi: 10.1016/j.enbuild.2008.11.007.

Philip, J.R., De Vries, D.A. 1957. « Moisture movement in porous materials under temperature gradients ». Transaction of American Geophysical Union 38 (2): 222–232. doi.org/10.1029/TR038i002p00222.

Rode, C., Peuhkuri, R., Lone, H., Time, B., Gustavsen, A., Ojanen, T., Ahonen, J., Svennberg, K. « 2005. Moisture buffering of building materials ». Nordic Innovation Centre Report: BYG-DTU R-126: 1601–2917.

Tran Le, A.D. 2010. « Etude des transferts hygrothermiques dans le béton de chanvre et leur application au bâtiment (sous-titre: simulation numérique et approche expérimentale) ». Thèse de doctorat, Reims : Université de Reims Champagne-Ardenne.

 
8:30 - 10:00Session T1.5: Climate change and bioclimatic design
Location: Crowne Plaza - De Burgh Room
Session Chair: Laura Carnieletto, University of Padova
Session Chair: Silke Verbruggen, Ghent University
Crowne Plaza - De Burgh Room 
 
8:30 - 8:48

An integrated approach to quantify the potential local climate mitigation of a district energy network compared to individual air conditioning systems.

G-E Kyriakodis1,2, Emmanuel Bozonnet1, Peter Riederer2

1University of La Rochelle; 2CSTB Sophia-Antipolis

Aim and Approach

(max 200 words)

The transition from building to district scale is supported numerically by the nascent field of Urban Building Energy Modelling. However, the concurrent assessment of building energy demand and local climate conditions is sparsely studied explicitly, while there is a lack of integrated tools embedding the modelling of district energy systems. This article presents a developed coupled model to account for building energy needs, urban heat island and site-specific effects, along with the district energy system operation. To illustrate the approach, we examine the mitigation potential of a district network under projected climate conditions for a city with an oceanic climate.

Scientific Innovation and Relevance

(max 200 words)

This paper demonstrates a coupled multi-model to account for urban building energy demand, UHI and site-specific effects as well as the integration of district energy systems to urban energy studies.

The developed methodology is based on a bottom-up approach where the explicit building footprints are enclosed by outdoor air cells of the urban canopy in which heat and mass transfer modelling techniques are employed under a zonal approach. The derived coupled urban canopy model is linked with a simplified urban boundary module and a vertical diffusion model. The spatial scale of the model corresponds to urban neighbourhoods while the temporal one to annual simulations given the limited execution time (23h/simulation). The model can be used either as a standalone in order to assess the urban thermal performance at various levels, or it can be readily decoupled to support a detailed meso-model.

Preliminary Results and Conclusions

(max 200 words)

The neighbourhood case study under future climate conditions for a city with an oceanic climate, examined the mitigation potential of a district energy network as a free on-site heat emitter, compared to individual energy systems, such as AC units, in terms of outdoor thermal comfort and energy efficiency. The simulation outcomes assessed a mitigation capacity of the cooling network close to 2%, considering the CDH as an outdoor thermal comfort indicator related to local climate modifications. The latter is also associated with a mean air temperature reduction of 0.4oC during the cooling period. However, the mitigation potential of the district energy system is correlated with a cooling penalty due to the ground losses of the tube circuit of approximately 18 MWh which cannot be balanced by the reduction of the cooling demand at the zone level due to the elimination of the rejected heat. Nevertheless, the increased cooling demand when the UHI effect is considered limits the cooling penalty.

Main References

(max 200 words)

1. Santamouris, M. (2020). Recent progress on urban overheating and heat island research. Integrated assessment of the energy, environmental, vulnerability and health impact. Synergies with the global climate change. Energy and Buildings, 207.

2. Gros, A., Bozonnet, E. and C. Inard (2014). Cool Materials Impact at District Scale—Coupling Building Energy and Microclimate Models. Sustainable Cities and Society 13, 254–266.

3. Kyriakodis, G-E., 'Development of a coupled simulation tool for urban building energy demand, district energy systems and microclimate modeling', PhD Thesis, 2020

4. Kyriakodis, G-E., et. al., "Quantifying the Impact of Urban Microclimate in Detailed Urban Building Energy Simulations.", IBPSA proceedings, 2019.

5. Riederer, P., Partenay, V., Perez, N., Nocito, C., Trigance, R. and T. Guiot (2015). Development of a Simulation Platform for the Evaluation of District Energy System Performances. Proceedings from BS2015: Building Simulation Conference. Hyderabad (India), 7-9 December 2015

6. Reinhart, C. F., et. al.,‘Urban building energy modeling–a review of a nascent field’. Building and Environment, vol. 97, 2016

7. Perera, A., et. al., “Quantifying the impact of urban climate by extending the boundaries of urban energy system modeling,” Applied Energy, vol. 222, pp. 847–860, 2018.



8:48 - 9:06

Building Performance Simulation to support tree planting for cooling need reduction: a machine learning approach

Massimo Palme1, Claudio Carrasco2, Riccardo Privitera3, Daniele La Rosa3

1Universidad Católica del Norte, Chile; 2Universidad de Valparaíso, Chile; 3University of Catania, Italy

Aim and Approach

(max 200 words)

Greening the city is recognised as a main strategy to improve cities liveability, outdoor environment and buildings’ energy efficiency in summer (Ng et al. 2012). A lot of research has been conducted on the topic of green urban environment simulation, especially in terms of shadows (Balogun et al. 2014, Laband and Sophocleus 2009), however most of these works used simplified models not considering the boundary conditions introduced by the nature of the urban planning problem. Only few attempts to cope with concrete configurations have been done until the date. This work proposes a machine learning approach to predict, based on certain number of previously run simulations, the contribution of trees’ shadows to cooling needs reduction in Mediterranean climates. This procedure can allow urban planners to evaluate a specific situation in terms of some easily observed parameters (building shape, type of trees, distance from the main façade, orientation, number of façades shadowed) and to obtain an estimation of cooling reduction or a classification in ranges of effectiveness (e.g. very poor, poor, medium, good, very good) of the configuration examined. Urban planners compare the resulting savings with other benefits and the cost of implementation of the green infrastructure.

Scientific Innovation and Relevance

(max 200 words)

Machine learning refers to the capability of an algorithm to learn from some available data and to develop a strategy to predict continuous or categorical values of a variable from other variables used as predictors. There are many algorithms that can be used to learn from data, an in some cases best results are obtained by using a combination of different algorithms (ensemble). Machine learning has been already used in urban planning problems (Oh et al 2006, Liu et al. 2017, Ye et al. 2019), suggesting that the approach can be very helpful for stakeholders. In this work, four different algorithms (knn, random forest, glm and loess) are tested as well as the ensemble of all of them, both considering a continuous and a categorical evaluation. Software R is used to test the performance of the algorithms and to visualize the results. The sensitivity, specificity and global accuracy of the different algorithms used can be compared. The approach is capable to be extended by the inclusion of new observations or new parameters to be used as predictors, resulting in a very flexible too to estimate the saving that can be obtained in each configuration tested.

Preliminary Results and Conclusions

(max 200 words)

First attempts in using this methodology show that if a prediction in terms of a continuous variable (cooling needs or energy savings of a specific configuration) is difficult (root mean square error of about 30%), a categorical evaluation can be obtained with an accuracy of about 95% with a single threshold value and about 70% with a five-categories classification. Such a result is useful for planners, who often take the decision in function of the question: is effective (in this configuration) to plant trees (or not)? Machine learning approach can answer to this question with a 95% of accuracy once established the threshold value (i.e. the saving that permits to equilibrate the cost-benefit analysis result). Among algorithms, random forest seems very interesting because of the high sensitivity (it assures that the minimum performance is achieved) and because the indication of the variable importance, that is a very useful result to be taken in consideration for future planning decisions.

Main References

(max 200 words)

Balogun, A.A., Morakinyo, T.E., Adegun, O.B. (2014). Effect of tree-shading on energy demand of two similar buildings. Energy and Buildings 81, 305-315

Laband, D., Sophocleus, V. (2009). An experimental analysis of the impact of tree shade on electricity consumption, Arboriculture and Urban Forestry, 35, 197-202.

Liu, L., Silva, E., Wu, C., Wang, H. (2017). A machine learning-based method for the large-scale evaluation of the qualities of the urban environment. Computers, Environment and Urban Systems. 65, 113-125.

Ng., E., Chen, L., Wang, Y., Yuan, C. (2012). A study on the cooling effects of greening in a high-density city: An experience from Hong Kong. Building and Environment 47, 256-271

Oh, J., Hwang, J.E., Smith, S., Koile, K. (2006). Learning from main streets. A Machine learnign approach identifying neighborhood comercial districts. Innovations in Design and Decision Support Systems in Architecture and Urban Planning.

Ye, Y., Richards, D., Lu, Y., Song, X., Zhuang, Y., Zeng, W., Zong, T. (2019). Measuring daily accessed street greenery: A human-scale approach for informing better urban planning practices. Landscape and Urban Planning 191



9:06 - 9:24

Development and analysis of a metric to manage overheating risks in residential energy codes

Rasoul Asaee, Alex Ferguson

Natural Resources Canada, Canada

Aim and Approach

(max 200 words)

The objective of this study was to propose a performance compliance requirement that will reduce the risks of overheating in homes by limiting design choices that are well understood to contribute to overheating.

We developed an archetype home to examine how solar gains for different glazing areas, different orientations, and various specifications for window solar gains. We also examined how predictions about cooling loads could vary between different building simulation platforms. We used 240 archetypes to evaluate the impact of the overheating test on home design. The 240 archetypes represent contemporary housing in eight major housing markets across Canada.

Scientific Innovation and Relevance

(max 200 words)

In cold climates, health and economic concerns continue to focus attention on occupants' comfort and energy consumption in winter rather than summer. For years, builders tend to increase solar gain through windows as a low-cost means to reduce the heating energy consumption in buildings. As the buildings become more energy tight, the risk of overheating during the summertime increases substantially. If designers do not consider the implications of adverse solar gains in summer, these homes may require significant cooling loads, and in extreme conditions, the heat stress caused can lead to premature death. Code officials asked authors to develop a metric to prevent the overheating risks in new Canadian residential buildings. We used building performance simulation to develop a workable solution that is easy to understand for the industry and assessed the impact of the new metric on building design.

Preliminary Results and Conclusions

(max 200 words)

Our results show that archetypes with small fenestration and door to wall ratio (FDWR < 10%), and low- to mid-gain windows generally comply with the requirement. As expected, archetypes that have higher windows area are less likely to comply with the overheating requirements. Likewise, the likelihood of compliance decreases in archetypes suing high-gain windows. For example, none of the archetypes with FDWRs above 30% complied with the requirement as designed; nor did any of the archetypes with very high gain windows (SHGC > 0.6).

This work led to the addition of an overheating metric for the first time in a Canadian building code. This requirement affects design choices in homes with high window areas. In such houses, the requirement can be met by choosing low solar-gain windows. Reducing window area, relocating east and west-facing windows to north and south facades, and installing overhangs also help homes comply. Authors recommended against permitting builders to install air-conditioning as an alternate means of compliance.

Main References

(max 200 words)

Environment and Climate Change Canada (2016). Pan-Canadian Framework on Clean Growth and Climate Change: Canadas plan to address climate change and grow the economy. Environment and Climate Change Canada.

Parekh, A., R. Charron, S. Poirier, and L. Roux (2018). Testing of HOT2000 version 11 in accordance with ASHRAE standard 140-2014. In Proceedings of the eSim 2018 Conference. Montreal, QC (Canada), 9-10 May 2018.

Crawley, D. B., Lawrie, L. K., Pedersen, C. O., & Winkelmann, F. C. (2000). Energy plus: energy simulation program. ASHRAE Journal, 42(4), 49-56.

NRCan (2018b). EnerGuide in Canada, Natural Resources Canada: Office of Energy Efficiency. Available online at www.nrcan.gc.ca/energy/products/energuide/12523.

 
8:30 - 10:00Session T1.6: Ensuring high quality building simulations
Location: Crowne Plaza - Arnulf Room
Session Chair: Jérôme Le Dréau, La Rochelle University
Session Chair: Lien De Backer, Ghent University
Crowne Plaza - Arnulf Room 
 
8:30 - 8:48

Faster computation of g-functions used for modeling of ground heat exchangers

Jeffrey Spitler, Jack Cook

Oklahoma State University, United States of America

Aim and Approach

(max 200 words)

Temperature response functions, known as g-functions, are a computationally efficient method for simulating ground heat exchangers (GHEs), used with ground-source heat pump (GSHP) systems as part of a whole-building energy simulation. In fact, at present, there are no other methods that have sufficient accuracy and are fast enough to simulate a ground-source heat pump system in a whole-building energy simulation.

The concept, mathematical derivation and an implementation of a g-function calculation program were developed by Claesson and Eskilson (1985). More recently Cimmino (2018a, 2018b, 2019) developed an open-source g-function calculation tool known as pygfunction. This tool offers great flexibility for the user to compute g-functions for specific configurations of boreholes. However, for large borehole configurations (with ~1000 boreholes), the required time to compute a single g-function can take several hours, and the required RAM can be on the order of 100 GB, greatly exceeding most desktop PCs. In order to develop libraries of g-functions and training sets for machine learning approaches, we are computing hundreds of thousands of g-functions. This paper describes further development of Cimmino’s methodology to speed the computation and reduce the memory requirements.

Scientific Innovation and Relevance

(max 200 words)

Dusseault and Pasquier(2019) demonstrated use of artificial neural networks to compute g-functions. 500,000 g-functions computed for fields of up to 10 boreholes were used to train the neural network. Pasquier (2019) has estimated that a million g-functions might be needed train a neural network. As described by Spitler, et al. (2020) the computing time and memory scale approximately with the square of the number of segments used. Each borehole is divided into multiple segments treated as finite line sources and the accuracy depends on the number of segments used. To compute g-functions for ~1000 borehole configurations with deep (~400m) boreholes even the resources of our university’s high-performance computing cluster are insufficient, as we have very few nodes with available RAM exceeding 256 GB.

Therefore, any effort to develop neural network training sets, or even libraries of g-functions that include very large borehole configurations will require development of an improved tool that is faster and uses less memory than pygfunction. This is also necessary for individual users wishing to compute custom g-functions on their desktop PC. The work described in this paper represents a significant improvement in both speed and memory requirements.

Preliminary Results and Conclusions

(max 200 words)

At the time of this writing, we have obtained about a 2.5-fold increase in computational speed for borehole fields with 3000-5000 segments. (This work was done on a desktop PC with 16 GB RAM, limiting the size of the borefield that could be analyzed.) For the case with 3000 segments, the memory requirement is reduced by about 75%, but a more careful analysis will be done once we move back to the university’s high-performance computing cluster. To date, the primary improvements have been obtained by switching from Python to C++, streamlining the code, using hash tables to store segment-to-segment interactions, and taking advantage of multi-threading. Additional, more substantive changes are planned, which should provide further improvement. Even with the existing improvements, g-functions can be computed much faster with much less memory, allowing larger borefields to be analyzed on desktop PCs and more widely available, lower-memory cluster nodes.

Main References

(max 200 words)

Cimmino, M. 2018a. Fast calculation of the g-functions of geothermal borehole fields using similarities in the evaluation of the finite line source solution. Journal of Building Performance Simulation 11(6): 655-668.

Cimmino, M. 2018b. pygfunction: an open-source toolbox for the evaluation of thermal. eSim 2018, Montreál, IBPSA Canada. 492-501.

Cimmino, M. 2019. Semi-Analytical Method for g-Function Calculation of bore fields with series- and parallel-connected boreholes. Science and Technology for the Built Environment 25(8): 1007-1022.

Claesson, J. and P. Eskilson. 1985. Thermal analysis of heat extraction boreholes. Proceedings of 3rd International Conference on Energy Storage for Building Heating and Cooling ENERSTOCK 85, Toronto, Canada, Public Works Canada. 222–227.

Dusseault, B. and P. Pasquier. 2019. Efficient g-function approximation with artificial neural networks for a varying number of boreholes on a regular or irregular layout. Science and Technology for the Built Environment 25(8): 1023-1035.

Pasquier, P. 2019. E-mail. J. D. Spitler.

Spitler, J.D. J. Cook, X. Liu. 2020. Recent Experiences Calculating g-functions for Use in Simulation of Ground Heat Exchangers. Submitted to GRC Transactions.



8:48 - 9:06

Evaluating the impact of neighbouring structures on a high-rise residential block’s performance

Weijie Xu, Carlos Jimenez-Bescos, John Kaiser Calautit

University of Nottingham, United Kingdom

Aim and Approach

(max 200 words)

The work aims to analyse the impact of building locations and neighbouring buildings on its energy performance by undertaking parametric modelling. In this research, a 12-storey residential building was investigated using a validated Building Energy Simulation (BES) model. IESVE will be used to assess the energy performance of the residential building, which is a dynamic thermal simulation based on the modelling of the heat transfer processes between a building and its microclimate. The cities selected for this research are Copenhagen – Denmark, Beijing – China and Singapore, which represents three different climatic conditions: oceanic, humid continental and tropical climate, respectively. The effect of parameters such as surroundings’ number and positions were discussed. In total, over 180 scenarios were modelled to understand the influence of the variation of different parameters.

Scientific Innovation and Relevance

(max 200 words)

Urbanisation has increased rapidly in recent years, and more high-rise buildings are built to accommodate the increasing urban population. The energy used by buildings in the urban area accounts for over one-third of the total energy demand. The energy usage of high-rise buildings is much higher than the low-rise building. High-rise buildings affect the solar conditions and wind environment of the surrounding areas which can have positive and negative effects depending upon the site-specific circumstances. The use of multi-parameter optimisation approach for the building design can achieve considerable energy savings and cost reduction while improving thermal comfort. Factors or parameters that influence building energy consumptions includes type of energy used, altitude, location, fabric, building design, shape orientation, operation and technology usage and have been explored in the literature. A limited number of studies investigated the energy performance of high-rise residential buildings in different climatic conditions. Although previous works focused on the urban morphology effect, not many works assessed the influence on high-rise building energy performance. In addition, most previous studies focused on how the UHI phenomenon affect the heating and cooling performance of buildings. There is little study on the association between neighbouring high-rise structures and energy consumption.

Preliminary Results and Conclusions

(max 200 words)

Surrounding buildings could positively and negatively influence the central building’s performance, depending on the location and shading conditions. For a single building, the annual solar gain difference between Denmark and China was 46.2MWh, and the total energy load difference was 47MWh. Influence on the thermal comfort of the inhabitants was also evaluated. Under the same set conditions, there were great differences between PMV and PPD values among the three locations, so the indoor set conditions should be determined depending on the local environment. Multiple high-rise buildings with narrow spacing were observed to have the largest impact on the central building’s energy performance. Overall, the results indicate that the design and layout are important issues to consider for high-rise buildings as they can influence the energy use up to 14.35% when the central building was surrounded by eight double-height buildings with 15m spacing. The present work has shown the importance of considering the influence of neighbouring structures when performing energy simulations of high rise buildings.

Main References

(max 200 words)

Vallati, A., et al., On the Impact ofUrban Micro Climate on the Energy Consumption of Buildings.Energy Procedia, 2015. 82: p. 506-511.

Cheung, C.K., R.J. Fuller, and M.B. Luther, Energy-efficient envelope design for high-rise apartments.Energy and Buildings, 2005. 37(1): p. 37-48.

Raji, B., M.J. Tenpierik, and A. van den Dobbelsteen, An assessment of energy-saving solutions for the envelope design of high-rise buildings in temperate climates: A case study in the Netherlands.Energy and Buildings, 2016. 124: p. 210-221.

Mardookhy, M., et al., A study of energy efficiency in residential buildings in Knoxville, Tennessee.Journal of Cleaner Production, 2014. 85: p. 241-249.

Mardookhy, M., et al., A study of energy efficiency in residential buildings in Knoxville, Tennessee.Journal of Cleaner Production, 2014. 85: p. 241-249.

Zhai, Z.J. and J.M. Helman, Implications of climate changesto building energy and design.Sustainable Cities and Society, 2019. 44: p. 511-519.

Samuelson, H., et al., Parametric energy simulation in early design: High-rise residential buildings in urban contexts.Building and Environment, 2016. 101: p. 19-31.



9:06 - 9:24

Where HVAC models fail - a conceptual framework for extending effective HVAC modelling into early concept design of net zero buildings

David Rulff, Theodor Victor Christiaanse, Ralph Evins

University of Victoria, Canada

Aim and Approach

(max 200 words)

The performance gap between measured building performance and simulated results in practice is a well documented issue, with error derived from a variety of sources (including misapplied tools and methods, uncertainty in design parameters, stochastic variability in operation and occupancy controls, etc.) and related to different stages of a building project life cycle (conceptualization, detailed design, construction and occupancy).[1] Traditional bottom-up, deterministic modeling frameworks for building HVAC systems are misaligned with a performance-based design paradigm, especially in early stages where broad design spaces and significant uncertainty are present.[2] For building energy modellers, the extent to which available conceptual frameworks can adapt to these changing conditions needed to be evaluated, with a consistent methodology that captures top-down functional requirements and uncertainty in a parametric analysis. The goal of this study is to engage in dialogue with the broader energy modelling community by outlining a variety of conceptual frameworks for representing HVAC systems from literature and practice, with particular emphasis on their influence on the reliability in applied building performance simulation.

Scientific Innovation and Relevance

(max 200 words)

This study presents a summary and comparison of different conceptual frameworks for HVAC modelling with a focus on net-zero buildings. This has significant implications in the context of increasingly stringent performance-based Building Codes and Standards that aim to regulate the majority of building stock in many countries, in efforts to reduce the impact of building energy consumption and associated greenhouse gas emissions on climate change. Each framework is deconstructed into characteristic components that allow consistent comparison, including how they capture the over-arching design and process goals, functional requirements, performance requirements (and corresponding performance indicators); as well as their capacity to integrate verification methods, functional systems and sub-systems, and stochastic elements or agents.[2] Alignment with best practice building modeling methodologies, technical schema and practical considerations is explored through implementation of a series of test cases in EnergyPlus, drawn from literature on sources of HVAC modeling errors and industry testing protocols.[3][4] Recommendations for future research and refinement of a common conceptual framework for HVAC are compiled from the results.

Preliminary Results and Conclusions

(max 200 words)

Promising HVAC modeling frameworks are found as part of larger building simulation research works, especially from three diverse areas of study: characterizing problem spaces and conducting feature engineering for black box machine learning methods,[5] describing system objects and functional schema for detailed calibration of high fidelity models,[6] and decomposition of building systems into functional units for best practice building simulation.[2] The different frameworks were used to define and implement test cases with increasingly complex HVAC system configurations in EnergyPlus, within the context of a performance-based design paradigm. Preliminary results indicate that uncertainty can be mitigated using statistical methods from calibration research, while limitations due to over-specification or excessive detail can be mitigated by consistent hierarchical decomposition that allows sub-elements and sub-systems to be collapsed into less granular functional units. The connection to the top-down performance requirements can be maintained through the same functional units, also helping preserve interpretability for machine learning methods that may be applied.

Main References

(max 200 words)

[1] de Wilde, P. (2014). The gap between predicted and measured energy performance of buildings: A framework for investigation. Automation in Construction, 41, 40–49. https://doi.org/10.1016/j.autcon.2014.02.009

[2] Augenbroe, G. (2019). 10 The role of simulation in performance-based building. Building Performance Simulation for Design and Operation.

[3] Eisenhower, B., O’Neill, Z., Fonoberov, V. A., & Mezić, I. (2012). Uncertainty and sensitivity decomposition of building energy models. Journal of Building Performance Simulation, 5(3), 171–184. https://doi.org/10.1080/19401493.2010.549964

[4] Tian, W., Heo, Y., de Wilde, P., Li, Z., Yan, D., Park, C. S., Feng, X., & Augenbroe, G. (2018). A review of uncertainty analysis in building energy assessment. Renewable and Sustainable Energy Reviews, 93, 285–301. https://doi.org/10.1016/j.rser.2018.05.029

[5] Zhang, Y., O’Neill, Z., Dong, B., & Augenbroe, G. (2015). Comparisons of inverse modeling approaches for predicting building energy performance. Building and Environment, 86, 177–190. https://doi.org/10.1016/j.buildenv.2014.12.023

[6] Coakley, D., Raftery, P., & Keane, M. (2014). A review of methods to match building energy simulation models to measured data. Renewable and Sustainable Energy Reviews, 37, 123–141. https://doi.org/10.1016/j.rser.2014.05.007

 
10:00 - 10:30Coffee Break
Location: Belfry
Belfry 
10:30 - 12:00Session T2.1: Practice and industry related case studies
Location: Cityhall (Belfry) - Room 1
Session Chair: Eline Himpe, Ghent University
Session Chair: Iago Cupeiro, KU Leuven
Cityhall (Belfry) - Room 1 
 
10:30 - 10:48

Developing a simplified methodology for simulating energy performance of buildings with thermally activated building systems

Mohsen Sharifi, Josué Borrajo Bastero, Rana Mahmoud, Eline Himpe, Jelle Laverge

Ghent university, Belgium

Aim and Approach

(max 200 words)

Detailed building models allow the HVAC designers to find optimal solutions. However, more complexity in modelling will also result in more efforts for the designers in the component sizing procedure specially when the optimal design of the system is highly depended on the control system. In Thermally Activated Building Systems (TABS), which are embedded pipes in the concrete of the building structure, the role of control is pivotal and thus the control has to be simulated during the design. Therefore, the building model and optimal control has to be coupled to an optimisation algorithm for optimal component sizing. This makes a computationally heavy pre-design procedure. This paper addresses the need for a for a simplified methodology for modelling building with TABS. We calculated the dynamic hourly heating and cooling loads of three case studies with white-box method and used them in simplified resistor-capacitor (RC) model developed by the grey-box approach and the parameters of RC model were estimated by inverse modelling approach. The methodology was applied on three different case studies and the results imply that the developed model by proposed methodology can be confidently coupled to an optimal control to be used for sizing HVAC components.

Scientific Innovation and Relevance

(max 200 words)

1-An automated algorithm for modelling building with TABS

2-Taking the advantage of white-box modelling to have high accuracy

3- Dynamic thermal behavior of the building can be incorporated to the design procedure with a simple model

Preliminary Results and Conclusions

(max 200 words)

Using built-in Modelica libraries and prepared code, the building demand is calculated accurately and easily. Then, a simplified model is derived by the proposed methodology and optimal sizing of HVAC components can be achieved in the early stage of design without expensive mathematical calculations. The first simulation results show that the simplified model can predict the dynamic thermal behaviour of the building accurately and the designer can be confident about the sizing of components when suing the proposed methodology.

Main References

(max 200 words)

1- W. Boydens, D. Costola, A. Dentel, T. Dippel, L. Ferkl, A. Görtgens, L. Helsen, J. Hoogmartens, B.W. Olesen, W. Parijs, M. Sourbron, C. Verhelst, J. Verheyen, C. Wagner, REHVA Guidebook No. 20: Improved system design and control of GEOTABS buildings: Design and operation of GEOTABS systems, REHVA, Brussels, 2013. www.rehva.eu.

2- Sharifi, M., Mahmoud, R., Himpe, E., & Laverge, J. (n.d.). Interaction of GEOTABS and secondary heating and cooling systems in hybridGEOTABS buildings : towards a sizing methodology.

3- Sourbron, M. (2012). Dynamic thermal behaviour of buildings with concrete core activation. PhD thesis

4-Jorissen, F. (2018). Toolchain for Optimal Control and Design of Energy Systems in Buildings. (April). Retrieved from https://limo.libis.be/primo-explore/fulldisplay?docid=LIRIAS1652305&context=L&vid=Lirias&search_scope=Lirias&tab=default_tab&lang=en_US



10:48 - 11:06

Analysis of the thermal performance of a ground water storage cell with helical shaped pipe for ground source heat pumps

Marco Marigo1, Enrico Prataviera1, Sara Bordignon1, Michele Bottarelli2, Angelo Zarrella1

1Department of Industrial Engineering, University of Padova, Italy; 2Architecture Department, University of Ferrara, Italy

Aim and Approach

(max 200 words)

Ground Source Heat Pump (GSHP) systems are promising technologies that can reduce fossil fuel consumption and CO2 emission due to the air-conditioning in buildings. The advantages of this technology compared to air-source heat pumps are well-known. However, the installation of vertical ground heat exchanger is expensive, consequently alternative solutions are necessary.

In this work, a particular vertical ground heat exchanger for residential buildings is studied. It consists of a helical shaped pipe installed in a water tank (cell) buried into the ground. The water of the tank can be groundwater or greywater from the dwelling. The bottom of the cell is installed at about 3 m under the ground surface. Different cells with helical shaped pipe can be coupled in parallel to the heat pump that provides heating and cooling for the building.

The new system was installed in a residential building in Treviso (Italy) and its temperatures were monitored on the long-term. Numerical simulations in transient conditions via a commercial finite element software were carried out to analyse the thermal behaviour of the cell. The long-term performance of the system was also simulated through a numerical model named CaRM (Capacity Resistance Model), which was modified to simulate this system.

Scientific Innovation and Relevance

(max 200 words)

Ground heat exchangers for GSHP can be vertically or horizontally oriented. For vertical ground heat exchangers, deep vertical bores need to be drilled increasing the initial cost of the installation. In addition, deep bores (usually 100 m long) are not feasible in some locations due to geological and legal constraints. Horizontal ground heat exchangers are installed at shallow depths (usually less than 2 m) requiring significantly more surface. Moreover, decreasing the depth of installation, they are more affected by weather variations.

In the presented heat exchanger, the higher thermal capacitance of the water in the tank is exploited in order to store energy, limit the peak loads and establish suitable control strategies. The heat transfer between ground and tank is continuous, and it is not related to the operation of the system. The lower depth allows the installation without the necessity of legal permissions and the maintenance is easier. The initial cost for the installation is lower than a drilling for a common vertical borehole heat exchanger.

Preliminary Results and Conclusions

(max 200 words)

A model in a finite element software was built to analyse the thermal behaviour of the system in the short term. In particular, the transient response to a heat load profile of the whole system was investigated analysing the heat exchanged between cell and ground, in both heating and cooling mode. A sensitivity analysis on the main parameters (e.g. geometry and material of the tank, pitch of the helical shaped pipe, installation depth, ground thermal properties) was carried out studying the effect on the thermal performance of the system. Then, a capacitance-resistance model was also developed for long-term simulations.

Simulation results are in good agreement with field measurements. They show the relationship between the temperature change and the volume of water in the cell. In addition, the new system is also compared with a common double U-tube configuration in terms of thermal performance on the long-term and from the economic point of view. The economic analysis points out the lower cost of the new solution.

Main References

(max 200 words)

Warner J, Liu X, Shi L, Qu M, Zhang M. A novel shallow bore ground heat exchanger for ground source heat pump applications - Model development and validation. Applied Thermal Engineering 2020; 164:114460.

Zhang M, Liu X, Biswas K, Warner J. A 3D numerical investigation of a novel shallow bore ground heat exchanger integrated with phase change material. Applied Thermal Engineering 2019; 162:114297.

Bonamente E, Aquino A, Cotana F. A PCM thermal storage for ground-source heat pumps: simulating the system performance via CFD approach. Energy Procedia 2016; 101:1079-1086.

Lund JW. Geothermal heat pumps - an overview, Geo-Heat Centre Quarterly Bullettin 2001; 22:1–8.

De Carli M, Tonon M, Zarrella A, Zecchin R. A computational capacity resistance model (CaRM) for vertical ground coupled heat exchangers. Renewable Energy 2010; 35:1537-1550

Zarrella A, De Carli M. Heat transfer analysis of short helical borehole heat exchangers. Applied Energy 2013; 102:1477-1491



11:06 - 11:24

Borehole thermal energy storage integration: a case study

Jonas Cleiren1, Freek Van Riet2, Kristof Smits1, Wolf Nys1, Roel Vandenbulcke1, Ivan Verhaert3

1Hysopt NV, Antwerp, Belgium; 2Noven NV, Ghent, Belgium; 3EMIB research group, University of Antwerp, Antwerp, Belgium

Aim and Approach

(max 200 words)

In the past decades, a large number of geothermal energy storage systems like Borehole Thermal Energy Storage (BTES) and Aquifer Thermal Energy Storage (ATES) have been widely applied. However, these systems are rather complex to design and prone to design errors, often resulting in suboptimal systems mainly on a hydraulic and control related point of view. In order to obtain a well-functioning system despite the complexity, a case study is conducted to address various optimisation possibilities.

To optimise a BTES system, a case study is conducted using the simulation software Hysopt because it takes both the thermal, as well as the hydraulic and control behaviour into account. In the case study, the initial design of a BTES system is optimised by simulating variants with different thermal, hydraulic and control design choices and comparing the resulting performances with each other. The analysis takes into account different KPIs like the energy consumption/cost, CO2 emission and investment cost.

Scientific Innovation and Relevance

(max 200 words)

Geothermal energy storage systems are called complex because of the combination of multiple types of production units, the possible desired thermal balance of the ground, the different operating conditions and the control strategy. Because of the complexity, extensive professional knowledge is required to design and correctly simulate geothermal energy storage systems. Even when doing so, there will always remain opportunities for improvement.

The conducted case study starts with the optimisation of the distribution network with the end-units to decrease the return and/or supply temperature. Afterwards the hydraulic configuration and control strategy of the energy centre is optimised to increase the contribution of the heat pump, which results in reduced energy consumption and CO2 emissions. The remaining excess heat and/or cold is stored in the BTES. Depending on the difference between extracted and injected heat, the ground can be thermally imbalanced. To address this imbalance, a few alternatives are proposed to improve the thermal balance. In addition, optimisations to keep the investment cost as low as possible are also proposed.

Preliminary Results and Conclusions

(max 200 words)

The conducted case study, including simulation of thermal, hydraulic and control behaviour, resulted in different design options. Depending on the priority of the KPIs, the most suitable design can be chosen.

The different design choices are mostly focused on hydraulic configurations and control strategies, mainly because these aspects are often neglected. In the case study, the energy consumption can be reduced by 40%, the energy cost by 30% and the CO2 emission also by 30%. Furthermore, some design choices lowered the investment cost and improved the thermal balance of the soil.

From the analysis of the simulation results, it can also be concluded that the performance of the system with geothermal energy storage is very sensitive to small adjustments in the hydraulics and controls. Therefore, it is recommended to choose a more robust design, for instance one with relatively simplistic controls, to reduce the error sensitivity.

Main References

(max 200 words)

R. Vandenbulcke, “Hydronic Simulation and Optimisation”, University of Antwerp, 2013.

F. Van Riet, “Hydronic design of hybrid thermal production systems in buildings”, University of Antwerp, 2019.

F. Van Riet, R. Vandenbulcke, J. Cleiren, and I. Verhaert, “Hydronic Optimisation Of Hybrid Heating Systems: A Methodology Based On Base Circuits”, IBPSA Building Simulation 2019.

F. Van Riet, H. El Khaoui, F. Hulsbosch, G. Steenackers, and I. Verhaert, “Exploring the novel software Hysopt: a comparison of hydronic heat distribution systems of an apartment building”, 12th REHVA World Congress CLIMA 2016.

J. Cleiren, “Hydronic design of heat- and cold production systems with geothermal seasonal energy storage”, University of Antwerp, 2018.

X. Q. Zhai, M. Qu, X. Yu, Y. Yang, and R. Z. Wang, “A review for the applications of integrated approaches of ground-coupled heat pump systems”, Renew. Sustain. Energy, vol. 15, no. 6, pp. 3133-3140, 2011.

L. Gao, J. Zhao, Q. An, J. Wang, and X. Liu, “A review on system performance studies of aquifer thermal energy storage”, Energy Procedia, vol. 142, pp. 3537-3545, 2017.

M. Bloemendal, T. Olsthoorn, and F. Boons, “How to achieve optimal and sustainable use of the subsurface for Aquifer Thermal Energy Storage”, Energy Policy, vol. 66, pp. 104-114, 2014.



11:24 - 11:42

Towards a new simulation based hybridGEOTABS design methodology!

Alexander Jean Lucienne Berquin

Boydens Engineering, Belgium

Aim and Approach

(max 200 words)

Providing an easy-to-use method to determine the optimal system powers of hybridGEOTABS in a predesign stage. The new method is based on a design moment analysis and correlation analysis of a simulated database.

Scientific Innovation and Relevance

(max 200 words)

It could be possible to size the different components of hybridGEOTABS in a predesign stage based on correlations between peak demands and optimal system powers.

Preliminary Results and Conclusions

(max 200 words)

It was shown that it is difficult to define specific design conditions to size the hybridGEOTABS components. However, main circumstances could be distinguished for which the system powers are peaking.

Furthermore, It is clear that high correlations exist between peak demands and the optimal system powers in heating and cooling mode. This was also investigated for different climates.

Main References

(max 200 words)

Berquin, A. (2020). Towards a new hybridGEOTABS design methodology! Universiteit Gent.

Franziska Bockelmann, Stefan Plesser, & Hanna Soldaty. (2017). REHVA Guidebook No. 20—Advanced System Design and Operation of GEOTABS Buildings. REHVA.

Mahmoud, R., Himpe, E., Delghust, M., & Laverge, J. (2019). D2.2 A set of parametric geometries for the (sub)typologies studied. UGent.

Sharifi, M., Himpe, E., & Laverge, J. (2019). D2.1 An automated baseload search algorithm for GEOTABS sizing. Universiteit Gent.

 
10:30 - 12:00Session T2.2: Ensuring high quality building simulations
Location: Cityhall (Belfry) - Room 2
Session Chair: Frank De Troyer, KU Leuven
Session Chair: Nils Artiges, Univ. Grenoble Alpes, CNRS, Grenoble INP, G2Elab, F-38000 Grenoble, France
Cityhall (Belfry) - Room 2 
 
10:30 - 10:48

Investigation of the temperature-dependent conductivity towards improving energy performance of building

Anna Wieprzkowicz, Dariusz Heim

Lodz University of Technology, Poland

Aim and Approach

(max 200 words)

The aim of the study is to investigate the effect of the temperature-dependent thermal conductivity on energy demand. The analysis was performed for the basic test building composed of a single rectangular zone, based on the Case 900 from ANSI/ASHRAE Standard 140-2011 (ANSI/ASHRAE 2011). The analysis was conducted for three locations characterized by different climate conditions: Norway, Bergen - cold climate without a dry season and with cold summer; Romania, Bucharest - temperate climate without a dry season and with warm summer; United Arab Emirates, Abu Dhabi – hot desert climate.

Ten functions of temperature-dependent thermal conductivity were developed and tested using non-linear properties subroutine implemented in ESP-r. The results were compared with the constant values of thermal conductivity: the maximum and minimum values included in predefined functions.

Results were analysed in terms of heating and cooling energy demand, the temperature of the insulation layer and dynamically changing thermal conductivity values as well as parameters characterizing the dynamics of thermal properties switching.

Scientific Innovation and Relevance

(max 200 words)

Dynamic properties of building components are highly expected regarding overall energy performance (Jelle, Gustavsen, and Baetens 2010) and future construction technology (Berardi et al. 2018). In case of heat transfer through building construction two thermal properties are technically possible to be adjusted: capacity and con