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: 6th July 2022, 15:19:55 CEST

 
Only Sessions at Location/Venue 
 
 
Session Overview
Location: Cityhall (Belfry) - Room 2
Date: Thursday, 02/Sept/2021
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
 
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.

 
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
 
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 conductivity, or combined both as a so-called heat retention index

The technical solution of dynamic insulation materials (DIM), also named controllable insulation materials (CIM) is mainly based on pore (gas filles) structures. It should be noted that only radical changes in the conductivity can lead to the reduction in energy consumption.

One of the parameters which determine the overall performance of DIM is control strategies. The initial work e.g. (Park, Srubar, and Krarti 2015) have investigated a binary R-value control in which the thermal resistance of the wall is either “on” or “off”. Further research, (Rupp and Krarti 2019) investigated the improved strategy by using wall surface temperatures, the heating/cooling set-point temperature, and the temperature in the middle of the wall. It is found that adding a period during which the R-value of the wall can vary continuously within a defined range has the potential to modestly decrease the heating and cooling energy consumption.

Preliminary Results and Conclusions

(max 200 words)

The results of building energy performance equipped with dynamic insulation materials were presented in the paper. The numerical model was developed in ESP-r considering the different function of thermal conductivity versus temperature. The sudden and smooth changes in conductivity values were considered in case of heating/cooling energy demand. Analyses were performed for three geographical locations: Bergen, Bucharest and Abu Dhabi. For each location, the energy savings were determined and the best function was finally defined. The biggest difference in cooling demand was 50% for Bucharest and 25% for Abu Dhabi. In both cases, the rapid changes in lambda values gave better energy performance of the dynamic insulation in case of analysed building. It was also concluded that periodic increase of thermal conductivity has no beneficial effect of heating energy demand - in a heating season high thermal resistance is crucial.

Main References

(max 200 words)

Jelle, Bjørn Petter, Arild Gustavsen, and Ruben Baetens. 2010. “The Path to the High Performance Thermal Building Insulation Materials and Solutions of Tomorrow.” Journal of Building Physics 34 (2): 99–123. doi:10.1177/1744259110372782.

Berardi, Umberto, Lamberto Tronchin, Massimiliano Manfren, and Benedetto Nastasi. 2018. “On the Effects of Variation of Thermal Conductivity in Buildings in the Italian Construction Sector.” Energies 11 (4). MDPI AG. doi:10.3390/en11040872.

Park, Benjamin, Wil V. Srubar, and Moncef Krarti. 2015. “Energy Performance Analysis of Variable Thermal Resistance Envelopes in Residential Buildings.” Energy and Buildings 103 (July). Elsevier Ltd: 317–325. doi:10.1016/j.enbuild.2015.06.061.

Rupp, Shawn, and Moncef Krarti. 2019. “Analysis of Multi-Step Control Strategies for Dynamic Insulation Systems.” Energy and Buildings 204 (December). Elsevier Ltd: 109459. doi:10.1016/j.enbuild.2019.109459.



10:48 - 11:06

3D drone-based time-lapse thermography: a case study of roof vulnerability characterization using photogrammetry and performance simulation implications

Tarek Rakha1, Yasser El Masri1, Kaiwen Chen1, Pieter De Wilde2

1Georgia Institute of Technology, United States of America; 2University of Plymouth, United Kingdom

Aim and Approach

(max 200 words)

This paper investigates airborne time-lapse thermography using drones as a method of translating 3D envelope CAD models generated via RGB and IR photogrammetry into whole Building Energy Modeling (BEM) software. The goal is to develop a novel 4D approach that incorporates defects detected at varying situations and instances of time into comprehensive thermal profiles for envelopes. We propose the development of novel 3D thermography models constructed from time lapse IR image data collected using UAS to inform BPS envelope modeling inputs. A case study is presented for a courtyard building on a North American campus, where the research team employed a drone to fly in two path types, perimeter polygon and in a strip. The flights repeated in 2-hour intervals starting at 9 AM until 5 PM (5 flights). In this work, we are focusing on the roof as a building element that is typically assumed to perform uniformly and is neglected in as-built inspections due to the impossibility of perceiving the entire component without being significantly higher than it.

Scientific Innovation and Relevance

(max 200 words)

Multiple built environment applications have made use of thermography, mainly focusing on defect identification using perspectives from the IR spectrum. However, standard IR readings are typically undergone in singular points in time, when in several cases, such as varying pressure differences or latent heat gain, anomalies can only be revealed at specific times of the day, possibly in different seasons of the year. The pursuit of a time-series based envelope diagnosis is not new; it started in the early 80’s under the terminology “Transient Thermography,” which evolved into “Time Sequential Thermography” in the late 90’s, and finally to “Time Lapse Thermography” in the mid-2010’s onward. Therefore, this paper’s scientific contribution is evolving this concept through two proposed innovations: 1) developing a novel Time Lapse Thermography inspection methodology that employs drones to inspect building envelopes at different times during the day that characterize an envelope’s performance comprehensively without being constricted spatially; 2) employing drone-collected and geolocated RGB and IR images to build 3D envelope CAD models using photogrammetry, and introducing the concept of 3D thermography to identify envelope defects. The work’s relevance is the translation of such models into simulation software for more accurate and faster existing building envelop modeling.

Preliminary Results and Conclusions

(max 200 words)

We presented in this paper a novel workflow for 3D envelope modeling using aerial time-lapse IR data collection using UAS. A comprehensive roof thermal profile was developed for a case study building employing photogrammetry software Agisoft Photoscan, which generated temporal IR inspections of a building’s roof using multiple 3D thermography CAD models. The goal was to develop a building inspection framework that utilizes drones equipped with IR cameras to collect data time series, which in turn informs envelope performance modeling to accurately depict thermal resistance as well as anomalies for more accurate BPS. The paper concludes that on-site building envelope inspections are significantly enhanced by a time-based passive thermography audit approach that has spatial liberty due to the use of UAS and discussed the potential for integrating this technology effectively in BEM to inform both facilities management and retrofitting design. Future work should explore full envelope 4D CAD modeling in concert with thermography. Advances in this field are expected to leap the process of building envelope energy audits forward to become ubiquitous and informative to decision makers aiming to retrofit and manage our existing built environments to become significantly more highly performing.

Main References

(max 200 words)

Edis, Ecem, Inês Flores-Colen, and Jorge De Brito. 2015. “Time-Dependent Passive Building Thermography for Detecting Delamination of Adhered Ceramic Cladding.” Journal of Nondestructive Evaluation 34 (3): 1–16. https://doi.org/10.1007/s10921-015-0297-5.

Fox, Matthew, David Coley, Steve Goodhew, and Pieter De Wilde. 2015. “Time-Lapse Thermography for Building Defect Detection.” Energy and Buildings 92: 95–106. https://doi.org/10.1016/j.enbuild.2015.01.021.

Gharawi, Mohanned Al, Yaw Adu-Gyamfi, and Glenn Washer. 2019. “A Framework for Automated Time-Lapse Thermography Data Processing.” Construction and Building Materials 227: 116507. https://doi.org/10.1016/j.conbuildmat.2019.07.233.

Grinzato, E., V. Vavilov, and T. Kauppinen. 1998. “Quantitative Infrared Thermography in Buildings.” Energy and Buildings 29 (1): 1–9.

Rakha, T., & Gorodetsky, A. (2018). Review of Unmanned Aerial System (UAS) applications in the built environment: Towards automated building inspection procedures using drones. Automation in Construction, 93, 252-264.

Hobbs, Chris. 1992. “Transient Thermography.” Sensor Review 12 (1): 8–13.

Hoyano, Akira, Kohichi Asano, and Takehisa Kanamaru. 1999. “Analysis of the Sensible Heat Flux from the Exterior Surface of Buildings Using Time Sequential Thermography.” Atmospheric Environment 33 (24–25): 3941–51.

Ibarra-Castanedo, Clemente, Stefano Sfarra, Matthieu Klein, and Xavier Maldague. 2017. “Solar Loading Thermography: Time-Lapsed Thermographic Survey and Advanced Thermographic Signal Processing for the Inspection of Civil Engineering and Cultural Heritage Structures.” Infrared Physics and Technology 82: 56–74.



11:06 - 11:24

Dynamic modelling and comparison between transient step response of capacitive hygrometers and chilled mirrors

Ettore Zanetti, Rossano Scoccia, Marcello Aprile, Mario Motta

Politecnico di Milano, Italy

Aim and Approach

(max 200 words)

This manuscript presents the results of an experimental study carried out to compare the transient responses of three capacitive hygrometers with respect to three chilled mirrors. Several experiments were carried out changing the values of air flow rate, temperature, and relative humidity in the test chambers. The results of these experiments were used to derive different models of the sensors, from black box data driven models, to grey box models. These can be used to check and eventually reconstruct transient data operation of desiccant evaporative cooling heat exchangers which are inherently transient. The sensors were tested in the ReLab research group facility [1], two climatic chambers were used to simulate the different conditions, the sensors were installed in a long cylindrical duct with a 16cm diameter. The step analysis was carried out by having a fan actively driving air inside the duct and by rapidly moving one end of the duct from one chamber to the other at different conditions until a steady state was reached.

Scientific Innovation and Relevance

(max 200 words)

Desiccant Evaporative Cooling (DEC) systems have seen an increased interest in academia [2] and commercial applications [3] for Heating ,Ventilation and Air Conditioning (HVAC) applications. The core components of these systems are the direct or indirect evaporative cooler coupled with a desiccant component. Traditionally the process air goes through the desiccant component, which can be a rotary enthalpic wheel filled with silica gel or other desiccant materials, and after being dehumidified and heated up is cooled via the direct or indirect evaporative cooler [4]. However, in the last years more compact solutions that incorporate the evaporative cooling and the desiccant action at the same time were developed as shown in [5],[3]. These new heat exchanger designs do not allow a continuous operation as the enthalpy wheel, they are transient systems where the silica gel dehumidify the air moisture until being full of water, then they are regenerated and the cycles can repeat. This transient behavior on a macroscale raises the problem of having a reliable measurement of the moisture content at the outlet of the heat exchanger. This manuscript shows the transient response of capacitive and chilled mirror hygrometers, trying to develop a dynamic model to simulate the transient response.

Preliminary Results and Conclusions

(max 200 words)

The experiments were carried out for three air flow rates (100-360-500 kg/h), three values of temperatures (20-30-35) and three (20-35-60) values of relative humidity. The preliminary result analysis shows that the chilled mirrors are faster for coupled Temperature and relative humidity step changes, while for just a relative humidity change the two instruments perform in a similar fashion. This is due to the type of capacitive hygrometer tested that has a heavy metal head, drastically increasing its thermal inertia. Starting from the experimental data the dynamic models for the instruments will be developed and validated against experimental data.

Main References

(max 200 words)

[1] P. di M. Department of Energy, “ReLab.” [Online]. Available: http://www.relab.polimi.it/laboratorio/laboratorio/.

[2] Y. Yang, G. Cui, and C. Q. Lan, “Developments in evaporative cooling and enhanced evaporative cooling - A review,” Renew. Sustain. Energy Rev., vol. 113, no. May, p. 109230, 2019.

[3] M. Beccali, P. Finocchiaro, M. Motta, and B. Di Pietra, “Monitoring and Energy Performance Assessment of the Compact DEC HVAC System ‘Freescoo Facade’ in Lampedusa (Italy),” Eurosun Conf. Proc., pp. 1–8, 2018.

[4] X. N. Wu, T. S. Ge, Y. J. Dai, and R. Z. Wang, “Review on substrate of solid desiccant dehumidification system,” Renew. Sustain. Energy Rev., vol. 82, pp. 3236–3249, Feb. 2018.

[5] T. S. Ge, Y. Li, R. Z. Ã. Wang, and Y. J. Dai, “A review of the mathematical models for predicting rotary desiccant wheel,” vol. 12, pp. 1485–1528, 2008.



11:24 - 11:42

Improving the Reliability of theoretical approaches for hygrothermal characterization and modeling of building envelopes

Imane Oubrahim1,2,3, Thierry Duforestel1,3, Rafik Belarbi2,3

1EDF R&D, TREE EDF Lab Les Renardières, 77818 Moret-sur-Loing, France; 2LaSIE UMR 7356, CNRS, La Rochelle Université, Avenue Michel Crépeau, 17042 La Ro- chelle Cedex 1, France; 34ev Lab CNRS, Université de La Rochelle, Electricité de France EDF, Avenue Michel Cré- peau, 17042 La Rochelle Cedex 1, France

Aim and Approach

(max 200 words)

The prevailing thermal methods turned out to be insufficient to deal with recent hygrothermal development in the building industry. Furthermore, the recent advances in dynamic modeling and advanced hygrothermal measurements also show their limitations when applied to these problems (Duforestel 2015). To summarize the situation, the simulated results have been in disagreement with the ones measured, chiefly in dynamic configurations. The analysis of these results led us to two essential weaknesses in the current methods: an underestimation of the vapor permeability of materials (linked to an experimental bias), and ignoring the hysteretic nature of moisture sorption in hygrothermal models. Therefore, a national project (SmartRéno) aims to complement our theoretical and experimental background to produce reliable tools for hygrothermal simulation, by investigating and redefining four main characteristics of building materials: The water vapor diffusion coefficient, the gas and liquid relative permeabilities and the sorption hysteresis.

Accordingly, this article will, first, present the precedent works that led us to this project. Then, the problematics to which we expect to respond and the methodology to be used to achieve the objectives will be detailed. Finally, we will put forward the first results of the work in relation to the objectives of this project.

Scientific Innovation and Relevance

(max 200 words)

All of the work in this paper must lead to a complete corpus of hygrothermal characterization methods, accurate enough to meet the needs of hygrothermal studies, and to an updated heat and mass transfer simulation tool (SYRTHES, developed at EDF R&D) integrating these changes.

We will investigate the impact of changing each coefficient at a time in order to analyze and explain the impact of all individual changes on the overall behavior of the simulation tool. Then, we will integrate all the coefficients revisited in the tool and finally validate the latter by comparing it to existing static and dynamic experimental results.

Preliminary Results and Conclusions

(max 200 words)

A sorption hysteresis model has been progressively identified based on the literrature. It has been integrated into the simulation tool SYRTHES for coupled heat and mass transfers. A comparison between experimental and simulated results has been carried out with various versions of the SYRTHES model:

- With an average curve of the mais sorption curves;

- Pure Mualem model;

- Pure linear model;

- Mixed model.

This comparison made it possible to highlight the impact of taking this phenomenon into account on the different calculated potentials.

A new experimental method for measuring water vapor diffusion coefficient is being tested on a varied range of materials used for the construction and renovation of building envelopes.

It is based on the principle of the cup test method with an adaptation to measure the difference in gas pressure between the two faces of the tested sample.

These tests are also being simulated in order to estimate the impact of the transfer characteristics on the expected results. It is expected that this new testing process will allow to determine the water vapor diffusion coefficient with an higher accuracy and will also allow the measurement of the gas relative permeability.

Main References

(max 200 words)

-Mualem, Y. (1973). Modified approach to capillary hysteresis based on similarity hypothesis.

Water Resources Research, Vol. 9, No. 5.

- Mualem, Y. (1974). A conceptual model of hysteresis. Water Resources Research, Vol. 10, No. 3.

- Duforestel, T. (2015). Des transferts couplés de masse et de chaleur à la conception bioclima-

tique : recherches sur l’efficacité énergétique des bâtiments. Habilitaion à diriger des recherches, Faculté des Sciences et Technologies, Département de Mécanique.

- EDF, I. Rupp, C. Peniguel, Syrthes, version 4.3.6: https://www.edf.fr/groupe-edf/qui-sommes-nous/activites/notre-communaute-scientifique/syrthes.

- Projet SmartRéno (mars 2019 – juin 2021): https://smart-reno.recherche.univ-lr.fr/.

 
13:30 - 15:00Session T3.2: Ensuring high quality building simulations
Location: Cityhall (Belfry) - Room 2
Session Chair: Dorota Brzezińska, Lodz University of Technology
Session Chair: Ralph Evins, University of Victoria
 
13:30 - 13:48

FMI Co-Simulation between 2D/3D component models and HVAC/control models

Andreas Nicolai, Andreas Söhnchen

TU Dresden, Germany

Aim and Approach

(max 200 words)

Detailed construction and building component models, including hygrothermal porous material transport models, can be used to model a large variatiy of modern energy transfer and storage systems. These include heated concrete slabs, shallow soil heat collectors, heated wall layers, combined photovoltaic and construction panels etc. The interaction with connected HVAC systems/energy distribution systems and/or control models is, however, often limited in such tools. Using three distinct application cases, the article describes the extension of the hygrothermal transport model DELPHIN with an FMI co-simulation interface and the setup of a coupled simulation with external models. The article covers the some details of the implemenation, but also derived best-practice approaches on FMI co-simulation algorithms and parameters, suitable for the tested application scenarios.

Scientific Innovation and Relevance

(max 200 words)

Description of tested, practice oriented co-simulation cases, using a detailed sub-model (building component model/hygrothermal transport model) and external control/energy distribution model. Description and demonstration of consequenced from Co-Simulation algorithm and parameter selection. Derivation of best-practice recommendations for setting up such coupled simulations, and defined interfaces and coupling parameters.

Preliminary Results and Conclusions

(max 200 words)

Co-Simulation support and use successfully demontrated in quite different use cases. Illustration, that supporting even the most basic variant of the FMI co-simulation standart enhances functionality of isolated models significantly. Discussion of co-simulation parameters show, that for application cases in building energy simulation/energy supply system simulation, a simple Gauss-Seidel co-simulation type with moderate time step selection is usually sufficient.

Main References

(max 200 words)

FMI co-simulation standard

Nicolai, A. and Paepcke, A.Entwicklung der Kopplungstechnologie von Komplexmodellen für Bauteil-, Raum- und Gebäudesimulation mit Modelica-basierten Anlagen-, Regelungs- und Nutzermodellen, 2018, Technischer Report

Nicolai, A. and Paepcke, A.; Co-Simulation between detailed building energy performance simulation and Modelica HVAC component models, 2017, 12th International Modelica Conference, Prague



13:48 - 14:06

Disaggregation of digital meter data for synthetic load profile generation

Toon Bogaerts2,3, Stef Jacobs1, Sara Ghane2,3, Freek Van Riet1, Wim Casteels2,3, Siegfried Mercelis2,3, Ivan Verhaert1, Peter Hellinckx2,3

1Energy and Materials in Infrastructure and Buildings, University of Antwerp, Belgium; 2IDLab, University of Antwerp, Belgium; 3Imec, Belgium

Aim and Approach

(max 200 words)

Building simulations require accurate Synthetic Load Profiles (SLP) of electricity consumption to research interaction with the grid or coping strategies for appliance-induced overheating. This is only possible by means of empirically validated user behavior profiles, i.e. based on in situ measurements. Logging for each single appliance separately is, however, expensive and labor-intensive. This means that centrally measured data should be disaggregated into the data of individual appliances.

The aim of this research is therefore to evaluate two event-based Non-Intrusive Load Monitoring (NILM) techniques for data disaggregation for appliance recognition: classification trees and timeseries analysis using deep learning . Moreover, the compatibility of these both techniques with low temporal resolution of the measurements is verified. Finally, based on the results, the applicability of the NILM-techniques on the digital energy meters in Belgium is discussed.

A public labelled dataset is considered as case study. The dataset contains one-week measurements with state transitions of the individual appliances as labels. The dataset is separated in order to train, validate and test the NILM-techniques.

Scientific Innovation and Relevance

(max 200 words)

According to the European Commission, digitalization of the energy system is a necessity for the transition towards a sustainable future. In this context, the roll out of digital energy meters in Europe has started. The next step is to translate the digital meters into “smart” meters. While great efforts have been made in previous research -including to the level of commercially available tools-, existing sources lack objective evaluation of disaggregation techniques. Therefore, no reliable tools exist for central measurements for generating Synthetic Load Profiles.

Therefore, this paper discusses the development and evaluation of different NILM-techniques for user behavior profile applications. Moreover, it compares different temporal resolutions to take into account different read-out frequencies. Indeed, e.g. only the more recent digital energy meters in Belgium are equipped with the high-frequency read-out S1 gate, while previous versions are limited to a frequency of 0.1 Hz.

To establish disaggregation of appliances, we look to use beyond the state of the art time series classification techniques such as appliance fingerprinting, timeseries classification and feature extraction combined with classification trees. More specifically, the use of Long Short Term Memory cells will be used to analyze time series.

Preliminary Results and Conclusions

(max 200 words)

Preliminary research shows that an optimized decision tree classifier is able to identify appliances in a similar fashion as statistical methods. Feature engineering improved the performance of the tree. We look to further improve these result by using recurrent neural networks such as LSTM’s to extract complex features from the timeseries data. These features can be passed to a fully connected multilayer perceptron classifier to distinguish the different appliances. Furthermore, the influence of the sample rate did not affect the decision tree. This relation will be further analyzed to estimate the importance of the s1 gate. Finally, we will look into the possibility of continues labeling of timeseries with a relation between the hidden state of the recurrent neural network and the states of appliances. With these techniques we look to achieve 5%-10% better performance in means of accuracy beyond statistical methods.

Before the discussed algorithms can be applied for the generation of Synthetic Load Profiles, future work should focus on their applicability on buildings with other user behaviour and appliances than represented by the used dataset.

Main References

(max 200 words)

• Anderson, K. et al., BLUED: A Fully Labeled Public Dataset for Event-Based Non-Intrusive Load Monitoring Research, in proceedings of ACM SustKDD'12, 2012

• NGUYEN, M., et al. A novel feature extraction and classification algorithm based on power components using single-point monitoring for NILM. In: 2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE). IEEE, 2015. p. 37-40.

• KELLY, Jack; KNOTTENBELT, William. Neural nilm: Deep neural networks applied to energy disaggregation. In: Proceedings of the 2nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments. 2015. p. 55-64.



14:06 - 14:24

Measurement of the building envelope thermal performance in collective housings

Lorena de Carvalho Araujo1,2, Simon Thébault1, Laurent Mora2, Thomas Recht2

1CSTB, France; 2Univérsité de Bordeaux, France

Aim and Approach

(max 200 words)

Building energy efficiency is a key factor in reducing CO2 emissions and assuring the comfort level for inhabitants. Governments have been valorizing the energy performance standards through thermal regulations and economic incentives. These are often based on results from building simulation softwares, achieved during building design stage. However, the real thermal performance can significantly deviate from the predicted one [1]. It is important to have reliable performance indicators to assure new building quality and to estimate the gains accruing after renovation works. The application of an in-situ method after construction or retrofitting phases enables the measurement of such indicators, as the whole heat loss coefficient (HLC) [2] and the heat loss coefficient by transmission (Htr) [3]. Collective housing counts for an important part of building stock, for this reason, mature technologies to measure its thermal performance are necessary. The current paper studies the applicability of a short duration test for identifying the HLC and Htr in collective housings and how to optimize the test protocol.

Scientific Innovation and Relevance

(max 200 words)

There are different available methods in the literature for measuring the building envelope thermal performance (for instance: average method, energy signature, PSTAR, EBBE, co-heating, ISABELE, QUB, and others) [2],[3],[4],[5],[6]. They present variations concerning the mathematical approach, the duration, the protocol modalities and the applicability [7],[8]. Among those, methods like energy signature and EBBE can be applied to collective housing. However, they use static models, presenting long measurement periods that usually lasts for more than one season extending upto a period of few years. Presently, there are not short duration tests that have been validated regarding the HLC and Htr estimation quality for this building typology. The propose of the current paper is to study a dynamic approach using grey box models, that allows the reduction of test protocol for identifying the thermal performance of collective housing’s envelope. In addition, variations of the test protocol, allows the study of optimal test conditions applied virtually to a medium collective housing. Furthermore, the relevancy of test protocol is verified by its application in-situ in a real building. This research suggests an alternative to evaluate the whole building heat loss coefficient of collective housings, with measurements duration shorter than one week.

Preliminary Results and Conclusions

(max 200 words)

We modelled in a thermal dynamic simulation software (Pléiades + COMFIE) a collective housing from the Residence Figuières Vignettes in Feyzin, France. It presents 1300 m² divided in four floors and sixteen apartments, 21 thermal zones and the thermal properties of components are in a level of a retrofitted building. 336 variations from a protocol inspired by ISABELE method were applied to this model in order to study the impact of several key parameters of the protocol (duration, heating power, set point temperature, preheating) in the quality of Htr estimation.

The test duration and the temperature difference from the beginning and the end of the test were the most influent parameters in the quality of the Htr indicator. For durations equal or superior to four days of measurement, the tests presented a Htr bias inferior to 15% for moderate internal temperature variation.

Besides the virtual experiments, we applied a test into a real collective housing composed of three apartments located in Sallanches, France. The overall heat loss coefficients level of this building was measured using the SEREINE method for a period of one week. After two days of test, the results are stable and present an uncertainty inferior to 15%.

Main References

(max 200 words)

[1] Wang, Liping & Mathew, Paul & Pang, Xiufeng. Uncertainties in energy consumption introduced by building operations and weather for a medium-size office building. Energy and Buildings. (2012).

[2] Bauwens G. In Situ Testing of a Building’s Overall Heat Loss Coefficient – Embedding Quasi-stationary and Dynamic Tests in a Building Physical and Statistical Framework. Doctoral Thesis. (2015) .

[3] Thébault, Simon. Contribution à l’évaluation in situ des performances d'isolation thermique de l'enveloppe des bâtiments. Thèse de doctorat. (2017).

[4] Cohen M. et al., EPILOG Livrable n° 2 Rapport de synthèse sur la méthodologie employée avec tests sur cas d’étude théoriques par simulation. PACTE. (2017).

[5] Nordström, Gustav, Helena Johnsson, and Sofia Lidelöw. "Using the energy signature method to estimate the effective U-value of buildings." Sustainability in Energy and Buildings. Springer, Berlin, (2013).

[6] Wingfield, Jez, et al. "Whole house heat loss test method (Coheating)." Leeds Metropolitan University (2010).

[7] IEA Annex 58. Reliable Building Energy Performance Characterisation Based on Full Scale Dynamic Measurements. (2015)

[8] Roels, Staf, et al. "On site characterisation of the overall heat loss coefficient: Comparison of different assessment methods by a blind validation exercise on a round robin test box." Energy and Buildings 153 (2017).



14:24 - 14:42

Cooling demand reduction approaches for typical buildings in a future city district in mid-Sweden

Sana Sayadi, Abolfazl Hayati, Jan Akander, Mathias Cehlin

Universuty of Gävle, Sweden

Aim and Approach

(max 200 words)

The increase in population and living standards, as well as global warming and heatwaves due to climate change, have created a challenge to meet the cooling demand in buildings. Using currently available sources of energy endangers future energy security[1]. Therefore, implementing new approaches to reduce energy requirements in buildings to pave the path for energy transition is an area of interest. This study aims to analyze and minimize the cooling requirement for a multifamily building through simulations in a new city district in mid-Sweden. Buildings must meet the Near Zero Energy Building (NZEB) requirements based on the new Swedish National building regulations [2]. This study first explores the cooling demand of the building by means of simulations with IDA Indoor Climate and Energy (IDA-ICE) software, then investigates the effect of different mechanical ventilation strategies, window properties and orientations. The characteristics are aligned with Key Performance Indices (KPIs) which are based on the proposed list from IEA Annex 80: Resilient cooling of buildings. Climate files of normal and extreme conditions are considered for the simulations [3]. After implementing the changes in the building, results and their effect on cooling demand is investigated.

Scientific Innovation and Relevance

(max 200 words)

Fulfilling the latest building regulations and implementing the most energy-efficient characteristics in the building, aligned with Annex 80’s proposed KPIs help meeting the NZEB requirements. Performance of the multifamily building with focus on robustness and resilience for a future city district has to be considered. Implementing optimum building and window specification and using different climate files help fulfilling the future resilient NZEB buildings. Today’s residential buildings, mainly in Sweden, have been designed to fulfill heating requirements but are seldom designed and equipped with systems for space cooling. This study investigates the future cooling requirement in terms of building regulation requirement and future climate conditions containing heat-waves.

Preliminary Results and Conclusions

(max 200 words)

The cooling demand is expected to rise as the climate changes, therefore, buildings should be resilient to the future heat-waves. The chosen model meets NZEB requirements by implementing different optimized characteristics of a building aligned with Annex 80’s KPIs and Swedish National Building regulations. The results envision the minimum cooling demand through optimum combination of the building’s specifications in the new city district in mid-Sweden to provide the required comfort for the residents

Main References

(max 200 words)

[1] Z. X. Jing, X. S. Jiang, Q. H. Wu, W. H. Tang, and B. Hua, “Modelling and optimal operation of a small-scale integrated energy based district heating and cooling system,” Energy, 2014, doi: 10.1016/j.energy.2014.06.030.

[2] Boverket, ”Konsekvensutredning BFS 2020:4 Boverkets föreskrifter om ändring i verkets byggregler (2011:6) – föreskrifter och allmänna råd, BBR, avsnitt 5 och 9”, [In Swedish] Report on proposed NZEB building regulations version BBR 29, 2020.

[3] A. Machard, C. Inard, J.-M. Alessandrini, C. Pelé, and J. Ribéron, “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 (13), p. 3424, doi: 10.3390/en13133424.

 
15:00 - 16:30Session T4.2: Ensuring high quality building simulations
Location: Cityhall (Belfry) - Room 2
Session Chair: Alessandro Dama, Politecnico di Milano
 
15:00 - 15:18

Embedded single-board controller for Double Skin Facade : a co-simulation virtual test bed

Giovanni Gennaro1,2, Francesco Goia3, Giuseppe De Michele2, Marco Perino1, Fabio Favoino1

1Politecnico di Torino, Italy; 2Eurac Research, Italy; 3Norwegian University of Science and Technology, NTNU, Norway

Aim and Approach

(max 200 words)

Dynamic transparent facades are multi-functional building systems able to change their thermophysical properties (e.g. g-value) in response to external stimuli or control logics, in order to meet different requirements such as energy efficiency and occupant comfort (thermal, visual, IAQ, acoustic). During building operation, in order to optimize the façade configurations according to the various and sometimes conflicting requirements, the design and implementation of the control method and system becomes important to ensure the achievement of the desired performance. The aim of this paper is to describe a framework for the implementation of real-time embedded controller for transparent dynamic facades, applied to a simple case study of a small office environment equipped with a Double Skin Façade (DSF). The core of the controller is the Raspberry Pi 4, a low-cost platform with powerful processors and thanks to its small size it can be easily integrated inside the façade together with the embedded sensors. Several execution and computational tasks can be conducted on this system efficiently, such as data analysis, building energy balances estimation and façade actuators control. Based on the experience and best practices found in literature both a calibrated white-box model developed in EnergyPlus and a rule-based controller have implemented.

Scientific Innovation and Relevance

(max 200 words)

Different control strategies could be implemented for DSF: from simpler rule-based one, to more complex model-based control strategies. The latter could be based on either reduced or physical models, and for both models, depending on the computational time compared to the control timestamp, either an embedded controller (integrated with the façade) or an external processor (exchanging sensed data and actuated variables with a local controller) could be adopted. The present work investigates the potential of embedding model-based and rule-based control strategy in an integrated controller within the façade, relying on low-cost IoT sensors and processors. For this sake, a real case study (i.e. DSF mock-up mounted on an outdoor facility of the Polytechnic of Turin with an operable venetian blind) is used to compare the performance of the two control strategies adopting the following steps: (i) the white model of the DSF (EnergyPlus based) is created and calibrated to experimental data; (ii) the model simulation is synchronized with real-time climate data and embedded in the controller; (iii) for each control time step the white model is adopted to perform control decision making to optimize a certain performance objective; (iv) this process is compared to rule-based decision based on best practices.

Preliminary Results and Conclusions

(max 200 words)

The development of a framework to test embedded controller for dynamic transparent facades presents different challenges and requirements: (i) the update of weather data acquired from a local climate station at each control time step, in order to perform model simulations with the real boundary conditions; (ii) the real-time integration of the measured data with the model; (iii) the computational time for the co-simulation of the models must be less than the time step of the control; (iv) the accuracy of simulated results. The main feature of this framework is the flexibility in terms of control strategies, limited only by the computational performance of the controller, which allows to implement control strategies based on physical, reduced models and simple rules. The computational performance of the Raspberry Pi allows to run several simulations (such as the number of the configuration that the dynamic facades can assume) within each control time step, to predict the optimal DSF configuration, providing very accurate results. Moreover, the integration in a single control system of sensors, control algorithms and actuators could be a robust solution for an embedded controller a dynamic façade, providing a more accurate prediction and decision-making support to the higher-level building control system.

Main References

(max 200 words)

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

2. Catto Lucchino E., Goia F., Lobaccaro G., Chaudhary G., Modelling of double skin facades in whole-building energy simulation tools: A review of current practices and possibilities for future developments. Building Simulation 12 (2019).

3. Aftab M., Chen C., Chau C.K., Rahwan T., Automatic HVAC control with real-time occupancy recognition and simulation-guided model predictive control in low-cost embedded system. Energy and Buildings 154 (2017).



15:18 - 15:36

Pyrano – A Python package for LiDAR-based solar irradiance simulations

Ádám Bognár, Roel C.G.M. Loonen, Jan L.M. Hensen

Eindhoven University of Technology, The Netherlands

Aim and Approach

(max 200 words)

Solar irradiance is a key input for modeling photovoltaic (PV) system performance and the influence of solar heat gains on a building’s energy balance. In the BPS domain, efficient techniques for including the effects of obstructions and reflections have been developed by daylight modeling researchers, but these are often only used to calculate daylight metrics in interior spaces. However, with some adjustments, such methods could also be applied on external built surfaces to calculate the solar irradiance input for PV or solar heat gain simulations.

The goal of this paper is to introduce Pyrano, a new Python package for simulating solar irradiance on external built surfaces. Pyrano consists of five modules:

- A geometry pre-processor that handles irradiance sensor-point placement over EnergyPlus surfaces.

- A LiDAR point-cloud pre-processor for applying geometrical transformations on the LiDAR point cloud to align its coordinate system with the EnergyPlus geometry.

- A Python wrapper to execute certain Radiance sub-programs, such as epw2wea, gendaymtx and dctimestep.

- An input-output module for results visualization and connecting inputs and outputs between solar irradiance and PV simulation software.

- A module for calculating flux-transfer coefficients from pre-processed LiDAR point clouds for efficient matrix-based (sub)hourly annual solar irradiance simulations.

Scientific Innovation and Relevance

(max 200 words)

If a building is situated in the built environment, its solar access is often influenced by reflections or shading by vegetation or other buildings. To be able to take this into account the geometry and reflectance properties of the surroundings need to be known, however, this input is often hard to acquire. The software presented in this work utilizes the 2.5 phase solar irradiance modeling method which was developed with a focus on the requirements of PV system and building solar heat gain simulations in urban context. It allows for taking into account shading and reflections based on the raw LiDAR point-cloud of the surroundings without the need for generating 3D surfaces nor conducting ray-tracing.

Simulation workflows for modeling PV together with a building situated in an urban environment are fragmented. Modeling of urban PV systems requires multidisciplinary knowledge from the modelers about simulating solar irradiance, building physics and electrical systems. Building energy modelers are usually architects, building engineers, or engineers specialized in BPS, rarely electrical engineers. This might have slowed the adoption of including PV for BPS investigations. In an attempt to address this issue, Pyrano bridges the gap between EnergyPlus (building energy), Radiance (irradiance) PVMismatch (PV power) simulations.

Preliminary Results and Conclusions

(max 200 words)

Pyrano was developed in a way that the inputs it uses are compatible with the inputs used by the state of the art ray-tracing software Radiance. This makes it easy to validate the results of the software. The simulations with the proposed method were compared to Radiance simulations with various realistic case studies, showing less than 4% deviation in the simulated annual solar irradiance.

The full-paper will explain the underlying modeling methods and will demonstrate Pyrano with a case study of calculating solar heat gains and PV yield of a building situated in a dense urban environment.

Pyrano is free and open-source. The source code and tutorials are available at: https://gitlab.tue.nl/bp-tue/pyrano. The python package can be installed from: https://pypi.org/project/pyrano/.

Main References

(max 200 words)

Subramaniam, S., 2017. Daylighting Simulations with Radiance using Matrix-based Methods.

Ward Larson, G., Shaskespeare, R., 2003. Rendering with Radiance. Morgan Kaufmann Publishers.

Reinhart, C.F., 2001. Daylight Availability and Manual Lighting Control in Office Buildings – Simulation Studies and Analysis of Measurements.

Mardaljevic, J., 2000. Daylight Simulation: Validation, Sky Models and Daylight Coefficient. De Montfort University Leicester.

Tregenza, P.R., Waters, I.M., 1983. Daylight coefficients. Light. Res. Technol. 15, 65–71.



15:36 - 15:54

A practical approach for modelling PV off-grid systems in EnergyPlus using post-processing of data to identify black out days

Valentina Tomat, Alfonso P. Ramallo-González, Antonio F. Skarmeta-Gómez

University of Murcia, Spain

Aim and Approach

(max 200 words)

Photovoltaic (PV) installations are considered a key element in the fight against energy waste, allowing users to self-produce the energy needed according to their specific demand. Their market spread increased in the last years, because of both the technical advances and more affordable costs. [1]

In remote areas, where the connection to the grid is not possible and it would bring a high cost to bring the power supply, the off-grid PV system is an excellent solution. [2][3] Nevertheless, the sizing of a standalone system in the literature is mainly defined through intuitive methods, numerical methods and analytical methods [4] while, when it comes to model a dynamic simulation, most software does not provide specific tools. Common energy simulation software like EnergyPlus and TRNSYS allow to design grid-tied systems and hybrid systems (grid-tied systems with a battery back-up to avoid outages), but there is almost no literature in how to model off-grid systems. This project aims to propose an equivalent method to simulate the off-grid photovoltaic system with the most popular software: EnergyPlus.

Scientific Innovation and Relevance

(max 200 words)

The main idea behind this paper is to use the simulator EnergyPlus to understand whether or not it is possible to model a standalone system starting from the design of a hybrid system, considering that the two systems are quite similar in design and components. The installation itself hardly provides enough energy to cover the demand throughout the year, because of weather unpredictability and because of unusual peak-demands. In a hybrid system, this scenario is solved by the eventual connection to the grid, that assures energy providing no matter the situation. In off-grid systems, when the installation does not cover the energy demand, black-out days occur.

Considered the similarity of the two situations, simulating a hybrid system, we can expect two main cases: In the first one, the building results to be autonomy all over the year, making the grid connection superfluous (when importation from facility does not occur at all, the building is considered able to operate also in off-grid conditions without outages [5]); in the second case, the model presents electricity coming from the utility: this energy can be converted in black-out days of an equivalent off-grid PV system.

Preliminary Results and Conclusions

(max 200 words)

To the best of the authors’ knowledge, the latter case has never been presented in a scientific paper. To test this method, the case study of an isolated house in the Region of Murcia, Spain, is presented. The building is modelled through SketchUp and Openstudio, while the dynamic energy simulation is obtained through the widely used software EnergyPlus. Results are given considering the number of days in which the battery charge at the end of the day is lower than 10%, i.e. the probability of a blackout day is high. Ten different scenarios are presented, differing in terms of electricity demand profile, PV peak power and battery storage capacity. Afterwards, the same scenarios are simulated with PVGIS, a tool implemented by the European Commission [6] to validate the results obtained with EnergyPlus. PVGIS is set to present the same electricity schedule and the same installation that has been used in EnergyPlus, to allow a more precise comparison. The comparison between the two methods shows good accuracy, inasmuch as the percentage of days varies between 0.5% and 11.9%, i.e., approximating by excess, between 2 and 44 blackout days of difference in the prevision.

Main References

(max 200 words)

[1] Barbose, G. L., Darghouth, N. R., Millstein, D., Spears, M., Wiser, R. H., Buckley, M. & Grue, N. (2015). Tracking the sun VIII: the installed price of residential and non-residential photovoltaic systems in the United States.

[2] Zahedi, A., 2006. Solar photovoltaic (PV) energy; latest developments in the building integrated and hybrid PV systems, Renewable Energy, 31 (5) (2006) 711-718.

[3] Bekele, G., Tadesse, G., 2012. Feasibility study of small Hydro/PV/Wind hybrid system for off-grid rural electrification in Ethiopia, Applied Energy, 97 (2012) 5-15.

[4] Khatib, T., Mohamed, A., Sopian, K., 2013. A review of photovoltaic systems size optimization techniques, Renewable and Sustainable Energy Reviews 22 (2013) 454-465.

[5] Brumana, G., Franchini, G., Perdichizzi, A., 2017. Design and Performance Prediction of an Energy+ Building in Dubai, ScienceDirect Energy Procedia 126 (2017) 155-162.

[6] Huld, T., Müller, R., Gambardella, A., 2012. A new solar radiation database for estimating PV performance in Europe and Africa, Solar Energy 86 (6) (2012) 1803-1815.



15:54 - 16:12

Initial validation of the one-diode photovoltaic model for the flexible panels

Dominika Knera, Dariusz Heim, Michał Krempski-Smejda

Lodz University of Technology, Poland

Aim and Approach

(max 200 words)

The flexible photovoltaic panels (FPV) became more and more popular in the building applications. In comparison with traditional, mainly crystalline silicon, the thin-film panels characterise by lightweight, low production cost or suitability for curved surfaces. The most popular thin-film PV are the Cadmium telluride (CdTe)/Cadmium sulphide (CdS) [1], as well as amorphous silicon and CIS/CIGS technologies [2]. In presented analysis flexible CIGS and semi-flexible crystalline silicon photovoltaic panels were tested experimentally in two configurations: free-standing (FSPV) and integrated with the wall (WIPV). Two aims of the study were formulated: to compare the performance of both PV panels and to verify the existing one-diode equivalent models implemented in ESP-r.

The experiments were conducted during selected days. Both PV configurations were tested parallel by measurements of power flow as well as the temperature of the modules. Additionally, the basic weather data were also registered, e.g. total and diffuse solar radiation, air temperature. The models of both installations (FSPV & WIPV) was developed in ESP-r using two one-diode photovoltaic models: Kelly’s and Watsun-PV model. The simulation results were compared with experiments.

Scientific Innovation and Relevance

(max 200 words)

Flexible PV technology has the potential to grow with a wide spectrum of application [3]. The advantage of them in comparison to stiff panels is visible in case of uneven surfaces. Additionally, building integrated flexible PV (BIPV) panels are usually much lighter than traditional. Those features make flexible PV more and more popular in building construction sector.

The existing PV models in ESP-r were validated for traditional crystalline PV modules equipped with glass sheets and aluminium frame [4]. The original part of this study is model validation for flexible thin-film PV under normal and extreme temperature. For FSPV the panel temperature slightly rises above the ambient air temperature because the effect of air cooling is high. When the PV panel is tightly joined with the building wall (WIPV) the risk of overheating rises rapidly and the effect of temperature on PV efficiency is much more visible. Additionally, the spectral characteristics of incident solar radiation will be analysed considering the visual and infrared part monitored on-site.

Preliminary Results and Conclusions

(max 200 words)

The models of both constructions (FSPV & WIPV) and two photovoltaic technologies (c-Si and CIGS) were defined in ESP-r. The simulations were conducted using two one-diode photovoltaic models: Kelly’s and Watsun-PV model. The initial results show the temperature and power flow for analyzed PV modules. The difference between power production and temperature is recognized. The experiments were done for clear and cloudy skies conditions. The final conclusion will be formulated based on the comparison between experimental and numerical results.

Main References

(max 200 words)

[1] Visa I, Burduhos B, Neagoe M, Moldovan M, Duta A. Comparative analysis of the infield response of five types of photovoltaic modules. Renew Energy 2016;95:178–90. https://doi.org/https://doi.org/10.1016/j.renene.2016.04.003.

[2] Pandey AK, Tyagi V V., Selvaraj JA, Rahim NA, Tyagi SK. Recent advances in solar photovoltaic systems for emerging trends and advanced applications. Renew Sustain Energy Rev 2016;53:859–84. https://doi.org/10.1016/j.rser.2015.09.043.

[3] Ramanujam J, Bishop DM, Todorov TK, Gunawan O, Rath J, Nekovei R, et al. Flexible CIGS, CdTe and a-Si:H based thin film solar cells: A review. Prog Mater Sci 2019:100619. https://doi.org/10.1016/j.pmatsci.2019.100619.

[4] Mottillo M, Beausoleil-Morrison I, Couture L, Poissant Y. A comparison and validation of two photovoltaic models. Can. Sol. Build. Conf., 2006.

 
17:00 - 18:30Session T5.2: Ensuring high quality building simulations
Location: Cityhall (Belfry) - Room 2
Session Chair: Andreas Nicolai, TU Dresden
Session Chair: Ralph Evins, University of Victoria
 
17:00 - 17:18

A parametric combined design and simulation tool for the optimisation of domestic hot water systems in residential care centres

Martijn Holvoet, Elisa Van Kenhove, Klaas De Jonge, Lien De Backer, Wim Boydens, Jelle Laverge

UGent / Archipelago

Aim and Approach

(max 200 words)

In this master dissertation research is conducted into the proper design and dimensioning of Domestic Hot Water (DHW) systems in public building

typologies. A basis for the optimisation of the design is created through the development of a flexible and parametric simulation tool in Modelica that can be used in the design phase. An extensive design study and research

into parameters and characteristics concerning the building, system and demand leads to assumptions of average values and data to fill in the information that is still unknown at this stage. Together with the integration of the general methods of dimensioning, the simulation tool can function with only a limited number

of input data and can therefore be used in the design

phase of DHW systems in public buildings.

Scientific Innovation and Relevance

(max 200 words)

The tightening of energy performance requirements effectuates the ever-improving energy efficiency in buildings. Among others, the insulation level and the airtightness of the building envelope have evolved considerably. Only in the field of DHW, there is comparatively little innovation. The energy demand for DHW remained nearly unaltered over the years and consequently starts to represent an important share of the total energy demand of buildings. It is a domain with little research and innovation, certainly concerning public building typologies. Regarding the building design, more attention should be paid to the optimisation of DHW systems. As there are many degrees of freedom concerning the configuration of these systems, tools that allow to make an informed choice for the specific configuration of the DHW system at an early stage can be of great importance. In addition, nowadays, also indicators such as energy use play a crucial role, where previously only comfort related aspects were considered as important. Concretizing performance factors of certain design proposals in the early phase can be useful. Normally, dimensioning is only done at a later stage of the design, at a time when modifications to the design already entail major implications and are therefore no longer possible.

Preliminary Results and Conclusions

(max 200 words)

A parametric simulation tool for DHW systems that can be effortlessly used in the design phase and requires only a few input parameters, is developed and it can have the potential to be of great importance in the design and optimisation of DHW systems in public building typologies.

However, this requires a complex and extensive integration of algorithms and a research into parameters and characteristics concerning the building, the DHW system and the hot water demand. On the basis of a virtual model, the operation of the DHW system can be assessed. The tool can allow concretizing of the performance factors of different proposals for the configuration of DHW systems. DHW system designers will be able to estimate the impact of design decisions and to reduce energy demand for DHW, while keeping an equilibrium between healthy, comfortable and energy efficient buildings.

In addition, the tool can also be used in the optimisation of various parameters, from thickness of insulation to the care and washing procedure. It also has opportunities in the field of Legionella decontamination.

It can have the potential to be of great importance in the optimisation of DHW systems and in the definition of energy-saving methodologies.

Main References

(max 200 words)

*Van den Abeele L., Dinne K., De Cuyper K. and Bleys B., ‘Best Beschikbare Technieken (BBT) voor Legionella-beheersing in Nieuw Sanitaire Systemen’. VITO & WTCB, 2017.

*Van Kenhove E., ‘Coupled thermohydraulic and biologic modelling of legionella Pneumophila proliferation in domestic hot water systems’, 2018.

*Deutsches Institut für Normung, ‘DIN 1988-300: Technische Regeln für Trinkwasser-Installationen - Teil 300: Ermittlung der Rohrdurchmesser’. Berlin, 2012.

*A. Bertrand, A. Mastrucci, N. Schüler, R. Aggoune, en F. Maréchal, “Characterisation of domestic hot water end-uses for

integrated urban thermal energy assessment and optimisation”, Applied Energy, vol. 186, pp. 152–166, jan. 2017.



17:18 - 17:36

Simulation of Legionella risks when restarting a sanitary sport facility installation after a period of inactivity during COVID-19

Elisa Van Kenhove, Lien De Backer, Jelle Laverge

Ghent University, Belgium

Aim and Approach

(max 200 words)

During the COVID-19 lockdown it was repeatedly reported in the media that the prolonged closure of buildings (e.g. hotels, sport facilities, student homes) is not without danger as stagnant water is an important risk factor for Legionella growth. LoWatter, a service of Ghent University, carries out scientific research and consultancy into Legionella in sanitary hot water systems [1]. Based on an in-house developed simulation tool, the Legionella concentration can be predicted dynamically in the entire hot water circuit [2]. The aim of the presented case study is to demonstrate what the consequences are of a temporary shutting down of a system with regard to the risk of a Legionella pneumophila contamination of the system. To do so, the simulation tool is applied on a fictive, but representative case of a sport facility. Parameters, such as number of changing rooms and showers were derived from a comparative study. The distribution system consists of a circulation loop, located in the basement, with vertical distribution to each changing room. Sizing of pipe diameters, insulation thickness, circulation pump and nominal power of the production unit was done within the simulation tool according to DIN1988-300 [3], [4].

Scientific Innovation and Relevance

(max 200 words)

The simulation tool applied for the described case study, is written in the Modelica language. This in-house developed tool is a parametric tool that allows to build up a simulation model of the hydraulic scheme quickly by defining building characteristics: in case of a sport facility such parameters are the number of changing rooms and number of showers. The sizing of all subcomponents present in the hot water system (production system, pump, pipes, valves,) is done automatically. Although this tool was used in this paper to study the impact of temporary shutting down, the tool can also be used in other situations that may cause Legionella contamination of in the water system. Examples are an improper balance of the sanitary hot water system and an undersized production system. This case-specific simulation model can then be used to first “virtually” test the effectiveness of possible solutions on a contaminated system (modifications on the system design, decontamination techniques), before applying this in practice. Based on the results, it is possible to provide advice on which case-specific measure(s) will ensure that the contamination disappears and does not reoccur. Furthermore, it allows a building owner to get a better understanding of the system.

Preliminary Results and Conclusions

(max 200 words)

The case study of the sports facility shows the effect of a prolonged stagnation of the water in a domestic hot water system. As expected, the combination of stagnation and the relatively high ambient temperatures that were present during April till August resulted in legionella growth in the system. The model also showed the importance of the correct application of proposed measures at the start-up of the system: flushing each tap point at a high temperature for a sufficiently long time.

Furthermore, the case study also shows the potential of the developed tool. The sizing that was calculated in the background of the tool was compared to a fully manual calculation for the same system and results in the same sizing of the system. There are still a few work points in the parametric tool such as the integration of the iterative calculation process in case the pressure drop in the pipes requires to an adjustment of the pipe diameter. This will be further improved.

Main References

(max 200 words)

[1] “Lowatter - Controlling Legionella in tapwater,” 2020. [Online]. Available: www.lowatter.com.

[2] E. Van Kenhove, L. De Backer, M. Delghust, and J. Laverge, “Coupling of modelica domestic hot water simulation model with controller,” in Proceedings of Building Simulation 2019 : 16th Conference of IBPSA, 2019, pp. 924–931.

[3] S. Kreps, K. De Cuyper, S. Vanassche, and K. Vrancken, “Best Beschikbare Technieken (BBT) voor Legionella-beheersing in Nieuwe Sanitaire Systemen,” 2017.

[4] DIN Deutsches Institut für Normung e.V., “DIN 1988-300 Technische Regeln für Trinkwasser-Installationen - Ermittlung der Rohrdurchmesser; Technische Regel des DVGW,” 2012.



17:36 - 17:54

Towards the integration of energy performance certificates (EPC) and simplified building performance simulations using machine learning: initial findings

Roberto Boghetti1, Roberto Rugani1, Marco Picco2, Giacomo Salvadori1, Marco Marengo2, Fabio Fantozzi1

1University of Pisa, Pisa, Italy; 2University of Brighton, Brighton, United Kingdom

Aim and Approach

(max 200 words)

A broad range of policies and supportive measures aimed at improving the performance of existing and new buildings has been introduced in the recent years. Among these, energy performance certificates provide a rating scheme to assess the energy efficiency of buildings based on quasi-steady state methods. The adoption of these certificates, however, is currently facing some critical issues, such as the lack of a quality control, a limited access to data for practitioners, and regional differences in the way the certificates are managed. Furthermore, the quasi-steady state calculation method used, while less onerous than a dynamic simulation, has a lower precision and still carries numerous overheads [1]. The most common risk is to use energy certification methods to predict the real consumption of buildings. Data-driven approaches may solve some of these problems and provide a faster yet powerful alternative to quasi-steady state methods which could also be easily integrated with existing building cadasters. The goal of this study is to examine the reliability of existing energy performance certificates and to investigate the possibility of using a data-driven approach, namely an artificial neural network (ANN), as an alternative to the current quasi-steady state method.

Scientific Innovation and Relevance

(max 200 words)

This study is a preliminary step towards a broader research intent: developing a simplified simulation tool based on machine learning to predict both the energy consumption of buildings and their associated energy performance score. Machine learning has been successfully used on a research level to predict energy consumption and carbon emissions of buildings[2-3-4], using both measured and simulated data. Given the complexity of the problem and the difficulty of gathering the needed data, however, the resulting models were always limited to the respective case studies and lacked the generality to be applied in practical situations. Focusing on energy performance certificates partially solves this issue as several public repositories of these certificates were made available by different european countries and institutions. To cope with the fact that these databases are not standardized, in particular for what concerns the descriptive parameters of the buildings, an intermediate step will be made to generate a surrogate model of each considered building using the available information, so that it will be possible to create a single predictive model despite having heterogeneous input data. In the view of the authors, this approach could represent a valuable and novel addition to the ongoing scientific discussion.

Preliminary Results and Conclusions

(max 200 words)

Preliminary results were obtained using both the old and new version of the Lombardy’s energy performance certificates database (CENED). The two databases, created according to two subsequent versions of the Italian norm, differ for the provided input data and for the calculation method. In both cases, the available certificates were vastly incorrect [5], with many entries incorrectly reported. The proposed data-driven model, which calculates the energy performance index (EPH) in the heating season, demonstrated high precision on the old database, with a mean error of around 10%. On the newer database, however, where some characteristics of the buildings were not available anymore, the resulting error was unacceptable, ranging around 40%. To demonstrate that the problem was due to the lack of important information, a third attempt to calculate the updated EPH value using inputs from the old database was made. Even if the number of available buildings in this case was smaller than in the previous attempts, the error, concentrated in highly efficient buildings, was reduced by 35%. The positive results on this initial step indicate that a data-driven approach to EPC calculation could yield reliable estimations and therefore represents a promising support to the current methodology.

Main References

(max 200 words)

[1] Ballarini, I., Primo, E. and Corrado, V., 2018. On the limits of the quasi-steady-state method to predict the energy performance of low-energy buildings. Thermal Science, 22(Suppl. 4), pp.1117-1127.

[2] Ahmad, M.W., Mourshed, M. and Rezgui, Y., 2017. Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption. Energy and Buildings, 147, pp.77-89.

[3] Paterakis, N.G., Mocanu, E., Gibescu, M., Stappers, B. and van Alst, W., 2017, September. Deep learning versus traditional machine learning methods for aggregated energy demand prediction. In 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) (pp. 1-6). IEEE.

[4] Boghetti, R., Fantozzi, F., Kämpf, J.H., Salvadori, G., 2019, Understanding the performance gap: a machine learning approach on residential buildings in Turin, Italy. Journal of Physics: Conference Series (1343), CISBAT 2019

[5] Khayatian, F. and Sarto, L., 2016. Application of neural networks for evaluating energy performance certificates of residential buildings. Energy and Buildings, 125, pp.45-54.



17:54 - 18:12

Interactions of building- / urban-, and multi-energy systems design variables

Adam Bufacchi1, Georgios Mavromatidis2, Arno Schlüter1, Christoph Waibel1

1Architecture and Building Systems, ETH Zurich, Switzerland; 2Sustainability and Technology, ETH Zurich, Switzerland

Aim and Approach

(max 200 words)

Significant synergies between the energy demand and supply side have been shown to exist which should be exploited in the design of low-carbon buildings and neighbourhoods by considering building design parameters and energy systems design parameters simultaneously, rather than addressing them sequentially (Waibel et al., 2019) (Ferrara et al., 2019). However, existing literature lacks an explicit quantification of such synergies, particularly at the building geometry scale. Therefore, this work aims to investigate the degree of parameter interdependence between parameters influencing energy demand (i.e. building construction, use, and geometry) and parameters defining the energy supply (i.e. the design of a neighbourhood’s decentralised multi-energy system).

We apply a Morris Screening on a wide range of parameters, which informs us through a qualitative ranking of these parameters’ importance. Subsequently, we compute first, second and total order Sobol indices: Global Sensitivity Analysis indicators, quantifying the parameters’ influence on the design output individually, when interacting with one-, or all other parameters respectively. Hereby we seek to quantify the degree of parameter interdependence. The workflow includes sampling real building geometries (LoD1 data of Zürich as case study), energy demand simulations with Energyplus/Honeybee, and multi-energy systems design optimisation using a Mixed Integer Linear Programming model.

Scientific Innovation and Relevance

(max 200 words)

Related work has investigated the significance of coupling the demand side with the supply side on larger district or urban scales, and with simplified, or archetypal geometrical parameters (Shi et al., 2020)(Mavromatidis et al., 2018). Our study, however, uses more detailed geometrical properties of individual buildings derived from existing building geometry data in its sensitivity analysis. The footprint and building height of randomly selected buildings are used to generate geometries of multi-story buildings with varying roof types and windows. Derived geometrical characteristics (such as compactness and significant faces) are calculated to understand the importance of different architectural features.

Furthermore, the sensitivities to the building- and energy parameters of not only the overall costs and emissions are analysed, as is typically the case, but also the sensitivities of the selection and sizing of the technologies in the energy hub are investigated.

Finally, due to the large number of dependent and independent variables considered in this study, we cluster several parameters into topical groups in the analysis (e.g. by overall performance of individual technologies, or by individual attributes such as size, efficiency or lifetime of the energy systems), which helps in understanding possible interactions between the energy demand and supply.

Preliminary Results and Conclusions

(max 200 words)

The preliminary results of the Morris screening are consistent with the existing literature: parameters directly affecting the energy demand, such as the overall geometry, ventilation, the climate, temperature setpoints and wall insulation appear to have a larger impact on the overall cost and emissions than technical energy system parameters such as investment costs or efficiencies of various technologies. In the subsequent Sobol Analysis, we will obtain quantitative measures on (first and second order) interaction effects between architectural design parameters and energy system design parameters.

Main References

(max 200 words)

Ferrara, M., Prunotto, F., Rolfo, A., & Fabrizio, E. (2019). Energy Demand and Supply Simultaneous Optimization to Design a Nearly Zero-Energy House. Applied Sciences. https://doi.org/10.3390/app9112261

Waibel, C., Evins, R., & Carmeliet, J. (2019). Co-simulation and optimization of building geometry and multi-energy systems: Interdependencies in energy supply, energy demand and solar potentials. Applied Energy, 1661–1682. https://doi.org/10.1016/j.apenergy.2019.03.177

Mavromatidis, G., Orehounig, K., & Carmeliet, J. (2018a). Uncertainty and global sensitivity analysis for the optimal design of distributed energy systems. Applied Energy, 214, 219–238. https://doi.org/10.1016/j.apenergy.2018.01.062

Shi, Z. ;, Hsieh, S. ;, Fonseca, J. A. ;, Schlueter, A., Shi, Z., Hsieh, S., & Fonseca, J. A. (2020). Interdependencies between the design of street grids and the cost-effectiveness of district cooling systems ETH Library 1 Interdependencies between the design of street grids and the cost-effectiveness of district cooling systems. https://doi.org/10.3929/ethz-b-000391818



18:12 - 18:30

Using a surrogate model to analyze the impact of geometry on energy efficiency of buildings.

Bhumika Bhatta1, Ralph Evins2, Paul Westermann3

1University of Victoria, Canada; 2University of Victoria, Canada; 3University of Victoria, Canada

Aim and Approach

(max 200 words)

Parametric exploration and optimization of building geometry is a powerful tool for designing energy efficient buildings. However, in practice this process is computationally expensive and time-consuming. In this research, we explore the use of surrogate models, i.e. efficient statistical approximations of ex-pensive physics-based building simulation models, to lower the computational burden of large-scale build-ng geometry analysis. For this purpose, we developed a novel dataset of 38,000 residential building models derived from real world floor plans from (Wu et al. (2019))[5] and train a surrogate model to emulate their simulated annual energy performance. We extract up to 20 parameters as surrogate model inputs to represent the building geometry and show that the trained surrogate model reaches a high accuracy (R2score = 0.999, MSE =0.007 and RMSE = 0.022) on test data. The current setup forms the basis for further research where the complexity of the building models will be increased.

Scientific Innovation and Relevance

(max 200 words)

Surrogates are the statistical models which can be used to provide rapid approximations of more expensive models. Surrogate models can be taken as an alternative approach to replace the detailed simulations with simplified approximate simulations, thereby sacrificing accuracy for reduced computational time. In this research work we are going to develop a surrogate model with two different approaches (physics-based and machine learning-based) which will approximate the impact of geometry on energy demand. Previous research work has been done on studying the impact of building geometry on its energy demand. For example, AlAnzi et al. [1] take the geometry of building into account for the energy performance analysis but consider the shape of façade only rather than the overall footprint. Most research studies sought to identify the relationship between the relative compactness or building volume and building energy loads [2],[3],[4] On the other hand, many research studies have considered hypothetical building shapes with constant floor area and height or constant floor area with varying heights among different shapes. The work presented in this paper will use a model, based on Building Technology Assessment Platform (BTAP) small and medium office building for Victoria, BC, Canada.

Preliminary Results and Conclusions

(max 200 words)

In this paper we provide a framework to develop neural network based surrogate models that predicts the EUI over different geometries. The frame work consists of conversion of 2D raster images of floorplans into 3D building simulation models, extraction of 20-building features for geometry, surrogate model training, and performance analysis of the impact of each feature. We developed the dataset consisting of 38,000 building simulation IDF files derived from real-world floor plans (Wu et al. (2019)). Our results for the training of the surrogate models show that off-the shelve neural network surrogate models pro-vided with manually engineered features are capable of emulating the simulation outcomes really well (R2score = 0.999, MSE = 0.007 and RMSE= 0.022) on test data. Overall, this paper shows that a simple machine learning model can perform very well in predicting energy use for various geometries, which provides architects with a great tool to get building performance estimates in real time while they are exploring various designs without the burden of simulating building designs individually.

Main References

(max 200 words)

1. Adnan AlAnzi, DonghyunSeo, and MoncefKrarti. Impact of building shape on thermalperformance of office buildings in kuwait. Energy Conversion and Management, 50(3):822–828, 2009

2. JosifasParasonis, Andrius Keizikas, Audron ̇eEndriukaityt ̇e, and Diana Kalibatien ̇e. Architec-tural solutions to increase the energy efficiency of buildings. Journal of civil engineering and management, 18(1):71–80, 2012

3. Werner Pessenlehner and Ardeshir Mahdavi. Building morphology, transparence, and energy performance. na, 2003

4. Carlo Ratti, Dana Raydan, and Koen Steemers. Building form and environmental performance: archetypes, analysis and an arid climate. Energy and buildings, 35(1):49–59, 2003.

5. Wu, W., X.-M. Fu, R. Tang, Y. Wang, Y.-H. Qi, and

L. Liu (2019). Data-driven interior plan generation for residential buildings. ACM Transactions

on Graphics (SIGGRAPH Asia) 38 (6)

 
Date: Friday, 03/Sept/2021
8:30 - 10:00Session F1.2: Ensuring high quality building simulations
Location: Cityhall (Belfry) - Room 2
Session Chair: Andrea Gasparella, Free University of Bozen - Bolzano
Session Chair: Aurelien Bres, AIT Austrian Institute of Technology
 
8:30 - 8:48

Effect of reduced air change rates on indoor air quality and air conditioning energy consumption in retail buildings

Konstantin Finkbeiner, Martin Kremer, Martin Rätz, Xuchao Ying, Paul Mathis, Dirk Müller

RWTH Aachen University, Germany

Aim and Approach

(max 200 words)

In the studies of [Mathis] and [Finkbeiner] the energy saving potential was investigated by measures such as reducing the air exchange rate in sales rooms and simultaneously increasing the water temperature of the refrigeration circuit. Savings of up to 35 % were proven

in the overall system.

Although the measures examined appear to be very promising, the condensation of water from moist air cannot be expected to be unproblematic. The reduction in fresh air volumes implies a reduced removal of moisture caused in shopping centers, especially by people. This can lead to an uncomfortable relative humidity level, even if the supply air humidity is controlled by an AHU.

This paper examines the effect of reduced air exchange rates on indoor humidity, assuming that only persons are the source of moisture. The minimum limit of the air exchange rate determined in [Mathis] is examined with regard to the aspect of comfortable indoor air humidity and, if necessary, further restricted.

For this purpose, the building model already presented in [Finkbeiner] is extended to include balancing of room air humidity. Moisture loads by people are implemented. In addition, the setting of the supply air humidity of the AHU is included in the analysis.

Scientific Innovation and Relevance

(max 200 words)

The low-order building model of [Lauster] is validated and is used in the context of simulative investigations of the energy demand of buildings. The model was primarily developed for the investigation of thermal energy demand of city districts and shows comparatively high simulation speed. Nevertheless, the accuracy of the simulation results is satisfactory. In the context of the consideration of city districts, the heat demand is the focus of the investigations. Thus, the building model of[Lauster] is also primarily intended for the sensitive change of state of the indoor air. Condensation effects, which mainly occur when using air water systems for indoor room

conditioning, are not considered. In this paper, the building model of[Lauster] is extended to include the consideration of moist indoor air in the energy demand calculation. For this purpose, the room air node is extended by the balancing of the water content in the moist air. On the other hand, the model of the air water systems is supplemented by balancing the water content of the humid air, so that the additional energy consumption that results from condensation during indoor air cooling can be taken into account.

Preliminary Results and Conclusions

(max 200 words)

The model of large retail buildings, especially shopping centres, presented by[Finkbeiner] was further calibrated on the basis of more detailed monitoring data, so that the accuracy of results could be further increased, as the simulation results shown in the attachment show. The simulated electrical demand of the monitored shopping center was primarily determined by converting the thermal demand. Looking at a period of six months, a deviation of 2% can be observed. A comparison of the simulated interior temperature with the measured one also shows a comparatively small deviation, see attachment. The water content of moist air indoors is largely determined by room air temperature. Thus, the calibrated model offers a good prerequisite for extending the air node model to include water content balancing of the moist indoor air. In addition, the model presented by[Finkbeiner] already takes into account the water content of the

outside air, the control of the supply air humidity via the AHU and the surface temperature of the air water systems.

Main References

(max 200 words)

[Finkbeiner] K. Finkbeiner, P. Mathis, F. Hintz, E. Bykhovskaya, L. Engelmeyer, D. Bohne and D. Müller, “Modeling a Building Energy System for Development of Energy Efficient Systems of Shopping Centers,” in Proceedings of the 15th IBPSA Conference, San Francisco, USA, 2017.

[Mathis] P. Mathis, H. Freitag, D. Hegemann, M. Schmidt and D. Müller, “New Concepts for the Ventilation of Shopping Centers: Reducing Air Change Rate, Applying Active Chilled Beams and Elevating Cold Water Supply Temperature,” Indoor and Built Environment, vol. 26, no. 2, pp. 08-225, 2017.

[Lauster] M. Lauster, J. Teichmann, M. Fuchs, R. Streblow and D. Müller, “Low order thermal network models for dynamic simulations of buildings on city district scale,” Building and Environment, p. 223–231, 2014.



8:48 - 9:06

Metrics for evaluating envelope performance in next generation energy codes

Rasoul Asaee1, Adam Wills2, Alex Ferguson1

1Natural Resources Canada, Canada; 2National Research Council, Canada

Aim and Approach

(max 200 words)

A performance path, which is a common approach for compliance in building codes, requires the whole building to perform up to a minimum limit. The performance path provides an opportunity for builders to use innovative design and technologies. This study aims to create criteria to capture the contribution of the building fabric and airtightness to the energy-efficient operation of the building while excluding the effects of mechanical equipment (e.g., space heating system type and ventilation system) and associated gains (e.g., standby losses of hot water tank). The metric should find a balance between the complexity of calculation and accuracy of output. Energy codes should not be dependant on building performance simulation software, and the building designers should be able to calculate the metric using a wide range of software options. Auhtors developed multiple metrics to assess the performance of envelope design and evaluated the impact of those metrics on building design in several climate zones.

Scientific Innovation and Relevance

(max 200 words)

Criteria for envelope improvement are considered desirable because these elements of a building are less frequently replaced and upgraded during the life of the building and can actively reduce the heat demand, whatever equipment is subsequently installed. Energy efficiency savings that must be achieved through envelope improvements alone (airtightness, insulation, glazing, solar design), and demonstrated through building performance modeling. The addition of a building envelope metric to the energy codes prevent compliance with the performance target by relying solely on a heat pump technology.

Preliminary Results and Conclusions

(max 200 words)

This paper presents the results obtained from the impact analysis of the proposed performance target in the new building code. The authors determined whether the new requirements set forward for the envelope metric can be achieved with technologies and approaches that builders have previously used in low-energy homes. We evaluated the energy savings and capital cost impact for achieving the envelope targets in different housing types and climate zones. Results indicate that the envelope metrics prioritizes investments in insulation, air-sealing, and energy-efficient windows. This philosophy presumes that cost savings can be found by reducing heating loads, thereby permitting the use of smaller and simpler heating equipment.

Main References

(max 200 words)

Government of British Columbia, "Energy Step Code - Building Beyond the Standard," 2019. [Online]. Available: https://energystepcode.ca/.

Natural Resources Canada, "Lessons learned and key findings from the ecoEII Net-Zero Demonstration and the R-2000 Net-Zero Energy Pilot," 2019.

BC Housing, "Energy Step Code 2017 Metrics Research," 2017. [Online]. Available: https://www.bchousing.org/research-centre/library/residential-design-construction/energy-step-code-2017-full-report&sortType=sortByDate.



9:06 - 9:24

Developments in simulation and evaluation of large-scale hot water tanks and pits in renewables-based district heating

Abdulrahman Dahash, Fabian Ochs, Alice Tosatto

University of Innsbruck, Austria

Aim and Approach

(max 200 words)

The efforts to phase-out the conventional fuels and achieve the decarbonization of the heating sector are notably increasing. Thus, the integration of renewable energy resources (e.g. solar energy, geothermal) found its place favorably in district heating (DH) whereby the share of renewables is gradually increasing in R-DH systems [1]. Yet, renewables integration can somehow alter the energy scheme and the operation leading to shortcomings (e.g. security of supply not met) [2]. Consequently, large-scale thermal energy storage (TES) is advantageous to bridge the gap between the renewables’ availability and heat demand eliminating the mismatching.

Accordingly, it is held that a large-scale and long-term TES enables a more flexible integration of renewables in DH systems and, as a result, has benefits in terms of lower fossils consumption, higher primary energy savings and lower CO2 emissions. Yet, the high capital cost associated to STES is frequently a major downside. Together with the space availability, complex planning layout and the presence of groundwater tables, these are the set of major challenges in STES domain to be tackled among others [2]. Thus, simulation-based analyses found its place favorably in the planning phase of such large-scale systems since its planning is considered a complex process.

Scientific Innovation and Relevance

(max 200 words)

To select properly the design, geometry and construction type for a large-scale TES, a number of inputs (hydro- geological factors, system characteristics, thermal losses, investment cost, etc.) are repetitively evaluated until a compromise between the technical performance and the economic feasibility is found [2]. Therefore, modeling is ideally suited to tackle the different challenges during planning to produce the optimal layout for the chosen TES.

Therefore, this work reports the development of large-scale TES numerical models in the framework of an international project entitled “Giga-Scale Thermal Energy Storage for Renewable Districts” [3] addressing the limitations, downsides and advantages based on experience in order to transfer the knowledge for other researchers and planners. Further, the work provides the major modeling parameters and their influence on TES operation and answers relevant questions such as to what extent and accuracy it is required to include these parameters. Moreover, the work compares the functionality of different techno-economic measures and addresses its applicability for large-scale TES. Such measures are energy efficiency, TES capacity efficiency, stratification and MIX numbers, thermocline thickness and rate of entropy generation.

Preliminary Results and Conclusions

(max 200 words)

In the modeling process hierarchy for the TES modeling, a pre-design tool is crucial for the early TES planning to examine TES potential. Next, the details are systematically included in the model for a detailed design. Later, it is necessary to examine the functionality of the integrated TES into a specific energy system and, herein, technology integration tools are required. As a result, the technology is thoroughly evaluated and the outputs are post-processed in the evaluation level. If the planners are not yet satisfied with the results, then TES planning reaches to the optimization level whereby different players (e.g. construction type, insulation thickness) are examined.

Within “Giga-Scale Thermal Energy Storage for Renewable Districts”, also co-simulations scenarios were proposed for large-scale TES. Thereby, a co-simulation scheme between a detailed design tool (i.e. COMSOL Multiphysics) and technology integration tool (i.e. Modelica/Dymola) was also tested and the results demonstrated the applicability of this approach. Yet, the feasibility of this method was limited due to the required computation efforts.

Main References

(max 200 words)

[1] Ochs et al., "Techno-economic planning and construction of cost-effective large-scale hot water thermal energy storage for Renewable District heating systems," Renewable Energy, vol. 150, pp. 1165-1177, 2019.

[2] Dahash et al., "Advances in seasonal thermal energy storage for solar district heating applications: A critical review on large-scale hot-water tank and pit thermal energy storage systems," Applied Energy, vol. 239, pp. 296-315, 2019.

[3] Giga_TES, “Giga-Scale Thermal Energy Storage for Renewable Districts”, https://www.gigates.at/, Flagship project (FFG, Energieforschung), 2019.



9:24 - 9:42

Energy flexibility quantification with integrated heat pump, floor heating system, and thermal storage in a school building

Navid Morovat1, José Agustín Candanedo1,2, Andreas K Athienitis1

1Concordia University, Montreal, Canada; 2CanmetENERGY, Montreal, Canada

Aim and Approach

(max 200 words)

School buildings are an important part of the building stock; they also represent a sizeable portion of the total energy use in the building sector. However, HVAC systems in schools are often non-optimized in terms of energy consumption and efficiency, and therefore, the energy cost of educational buildings is considerable. Thus, satisfying the increasing requirements of environmental performance standards –along with the need to enhance energy flexibility– is a challenging task[1-4].

While simulations have often been used to investigate energy consumption patterns in schools [5], there are relatively few publications on measured energy use in schools in general [6,7] and even fewer publications on new/low-energy schools. Considering that many schools need to be built in the near future, it is imperative to address this gap in data-based research on the energy performance and flexibility of new schools.

In this paper, an iterative calibration process is performed to evaluate the quality of grey-box models and identified parameters in a thermal zone with a floor heating system. The predictions from the model are then compared to experimental data and validated models are used to further study energy performance and energy flexibility of the thermal zone with floor heating in a school.

Scientific Innovation and Relevance

(max 200 words)

The case study school has been in operation since 2017, and it is a 100 % electric building. Features of the school include a high-temperature thermal storage device, local water-to-air heat pumps, and a water-to-water heat pump used for radiant floor heating. There are several sources of high-resolution data, including the BAS and dedicated electrical sub-meters.

This paper focuses on the evaluation of the different control strategies aimed at reducing peak demand and quantifying the energy flexibility potential of the thermal zone. The developed models are based on a data-driven grey-box model formulation and calibrated with measured data which is suitable for application in the context of demand-side management in Smart Grids.

Energy flexibility is an essential part of the solution to address the electrical grid’s challenges such as providing a contingency reserve to be used for emergencies. To address this need, real-time energy flexibility is needed to be predicted ahead of time or calculated continuously and available at short notice (e.g. 10 minutes) over a time duration of a few hours. Using the calibrated model, this paper investigates the application of a Building Energy Flexibility Index (BEFI) to quantifying real-time energy flexibility relative to a reference as-usual energy consumption profile.

Preliminary Results and Conclusions

(max 200 words)

The developed grey-box model shows acceptable accuracy for both the total and instantaneous heat demand in the building, making it suitable for the development of demand-side management control strategies in a Smart Grid context. This study also investigates the calibration of data-driven grey-box models for simulation of energy demand and energy flexibility of a thermal zone with floor heating in the school building.

This paper develops a methodology consisting of four steps: (1) modeling and calibration with experimental data, (2) flexibility characterization, (3) scenario modeling to assess the impact on electricity demand, and (4) evaluating the application of Building Energy Flexibility Index (BEFI) to quantifying real-time energy flexibility and enable interaction between building, aggregators and utilities.

Main References

(max 200 words)

1. Finck, C., R. Li, and W. Zeiler, Optimal control of demand flexibility under real-time pricing for heating systems in buildings: A real-life demonstration. Applied Energy, 2020. 263: p. 114671.

2. Hu, M., et al., Price-responsive model predictive control of floor heating systems for demand response using building thermal mass. Applied Thermal Engineering, 2019. 153: p. 316-329.

3. Jensen, S.Ø., et al., IEA EBC annex 67 energy flexible buildings. Energy and Buildings, 2017. 155: p. 25-34.

4. Reynders, G., et al., Energy flexible buildings: An evaluation of definitions and quantification methodologies applied to thermal storage. Energy and Buildings, 2018. 166: p. 372-390.

5. Dasgupta, A., A. Prodromou, and D. Mumovic, Operational versus designed performance of low carbon schools in England: Bridging a credibility gap. HVAC&R Research, 2012. 18(1-2): p. 37-50.

6. Van Dronkelaar, C., et al., A review of the energy performance gap and its underlying causes in non-domestic buildings. Frontiers in Mechanical Engineering, 2016. 1: p. 17.

7. Golshan, M., H. Thoen, and W. Zeiler, Dutch sustainable schools towards energy positive. Journal of Building Engineering, 2018. 19: p. 161-171.



9:42 - 10:00

Integrating energy systems into building design with Hive: Features, user survey and comparison with Ladybug and Honeybee tools

Christoph Waibel, Daren Thomas, Amr Elesawy, Illias Hischier, Linus Walker, Arno Schlüter

Chair of Architecture and Building Systems, ETH Zurich, Switzerland

Aim and Approach

(max 200 words)

Synergistic effects between the energy demand and supply side suggest that building energy systems should be treated as integral parts in the design of buildings (Ferrara et al. 2019, Waibel et al. 2019). In architectural practice and education, however, building systems are commonly regarded as to be specified by (HVAC) engineers to fit a given architectural design. To close this gap, we present a decision support tool that makes the most relevant aspects related to energy systems easily accessible to architects at a conceptual design stage. We discuss results from qualitative studies and semi-structured interviews with architecture students on their experience with performance-driven design and on their experience with the tool. From these surveys, we can identify common challenges that arise in an increasingly complex and technology driven architectural design process.

Scientific Innovation and Relevance

(max 200 words)

This study includes contributions in model development (decision support tool), as well as in empirical research (interviews and questionnaires). The decision support tool is implemented as a plug-in in Rhinoceros Grasshopper. The major innovation of the tool is its flexible software architecture that allows coupling to various third party and in-house model libraries. This framework is realized by establishing clean input-output relations with the introduction of a “distributor” component that processes all inputs into appropriate data types for the calculation models used. All results are then streamed back together and collided into a central results viewer. Thus, it leads to an easily accessible toolset with low entrance barriers, allowing an intuitive integration of energy systems into architectural design - a major difference to other existing workflows and tools. The empirical research with the architecture students is also adding novel findings to the building simulation research community, as it identifies real-world challenges that arise when integrating energy systems into architectural design processes.

Preliminary Results and Conclusions

(max 200 words)

First user tests of the new energy systems integrated design tool with architecture students have shown that the accessibility of novel decision support tools significantly impact design decisions made by architects. To foster the uptake of such tools, we found that (i) providing default values (such as for simulation model settings or technology parameters) but with the option to set custom values, (ii) visual representations (e.g. showing energy systems in 3D as part of the building design), (iii) as well as immediate performance feedback (e.g. implications of architectural design elements such as form, orientation or construction on energy systems design, cost and carbon emissions) are most vital. Finally, due to the growing complexity of architectural design processes with an increasing degree of specialized domain expertise becoming relevant, it is indispensable to provide a design framework that allows flexible compilation of third party model libraries packaged into one coherent architecture-focused design workflow.

Main References

(max 200 words)

M. Ferrara, F. Prunotto, A. Rolfo, E. Fabrizio, Energy demand and supply simultaneous optimization to design a nearly zero-energy house, Appl. Sci. 9 (2019) 2261, https://doi.org/10.3390/app9112261.

C. Waibel, R. Evins, J. Carmeliet, Co-simulation and optimization of building geometry and multi-energy systems: interdependencies in energy supply, energy demand and solar potentials, Appl. Energy 242 (2019) 1661–1682, https://doi.org/10.1016/j.apenergy.2019.03.177.

 
10:30 - 12:00Session F2.2: Ensuring high quality building simulations
Location: Cityhall (Belfry) - Room 2
Session Chair: Joel Neymark, J. Neymark & Associates
Session Chair: Ádám Bognár, Eindhoven University of Technology
 
10:30 - 10:48

CNN-based quick energy prediction model using image analysis for shape information

Manav Mahan Singh1, Philipp Geyer1,2

1KU Leuven; 2TU Berlin

Aim and Approach

(max 200 words)

An early stage of design requires a few hundreds of simulations to support informed decision-making for energy-efficient building design (Clarke & Hensen, 2015; Lee et al., 2016). However, high computational time and re-modelling efforts required by dynamic energy simulation tools limit their use at the early design stage (Geyer & Schlüter, 2014). It requires quick energy prediction approach integrated into the design process. Previously, other researchers have proposed use of data-driven approaches such as deep learning (DL) model and their integration into building information modelling (BIM) tool (Amasyali et al., 2018). A designer experiments with building shape, envelope and technical specifications at an early design stage (Picco et al., 2014). Thus, we aim to develop a DL model which predicts the energy demand for various combinations of building shapes and other design parameters. Since there is a lot of information which is uncertain at the early design stage, we aim to develop BIM-integrated tool to make probabilistic energy prediction based on the range of undecided design parameters (Singh & Geyer, 2019). The tool should be able to evaluate several design options for energy performance within a few seconds to make use of energy prediction results at the early design stage.

Scientific Innovation and Relevance

(max 200 words)

The building shape evolves continuously at early stages and representing it with a fixed set of parameters is cumbersome. However, we can represent a building having the same floor plan on each floor, by a two-dimensional image. We are using a convolutional neural network (CNN) to capture the information related to the building shape. Besides the building shape information, there is a set of technical specifications and other parameters which are adequately represented by numeric values. Thus, we need a model architecture which utilises both the information of building shape and other design parameters. We propose a CNN-DL model architecture, in which CNN captures the information from image (floor plan) and DL captures the information about technical parameters. Both models will be merged to get CNN-DL model, which will be trained to make quick energy predictions. The developed model will be useful for predicting energy demand of different building configurations within a few seconds. This reduction in time will make the energy prediction information available quickly as expected to make an informed decision at the early design stage.

Preliminary Results and Conclusions

(max 200 words)

The approach is tested on a medium-size office building in Munich. We developed the EnergyPlus model and calibrated against the real energy consumption of a three-storey office building. Then, it is extended to predict the energy demand of various shapes and combinations of design parameters. We generated the training dataset of 5000 samples and test dataset of 1000 samples. Building samples in both training and test dataset have random rectilinear floor plans. We trained CNN-DL model for several combination of hyper-paramters and the best model based on the least validation loss is selected. The model shows an accuracy of 0.983 in terms of R2 and root mean square error (RMSE) of 7 MWh/a.

We integrated these energy prediction model into a BIM tool to make energy prediction under uncertainty. The developed Approach makes probabilistic energy prediction five design options with 500 samples within a minute with the accuracy. Thus, in this research, we developed an approach to make use of energy prediction results to steer the design decisions at the early design stage.

Main References

(max 200 words)

Amasyali, K., Gohary, N., & El-Gohary, N. M. (2018). A review of data-driven building energy consumption prediction studies. Renewable and Sustainable Energy Reviews, 81, 1192–1205. https://doi.org/10.1016/j.rser.2017.04.095

Clarke, J., & Hensen, J. (2015). Integrated building performance simulation: Progress, prospects and requirements. Building and Environment, 91, 294–306. https://doi.org/10.1016/j.buildenv.2015.04.002

Geyer, P., & Schlüter, A. (2014). Automated metamodel generation for Design Space Exploration and decision-making – A novel method supporting performance-oriented building design and retrofitting. Applied Energy, 119, 537–556. https://doi.org/10.1016/j.apenergy.2013.12.064

Lee, B., Pourmousavian, N., & Hensen, J. L. M. (2016). Full-factorial design space exploration approach for multi-criteria decision making of the design of industrial halls. Energy and Buildings, 117, 352–361. https://doi.org/10.1016/j.enbuild.2015.09.028

Picco, M., Lollini, R., & Marengo, M. (2014). Towards energy performance evaluation in early stage building design: A simplification methodology for commercial building models. Energy and Buildings, 76, 497–505. https://doi.org/10.1016/j.enbuild.2014.03.016

Singh, M. M., & Geyer, P. (2019). Statistical decision assistance for determining energy-efficient options in building design under uncertainty. In P. Geyer, K. Allacker, M. Schevenels, F. De Troyer, & Pieter Pauwels (Eds.), 26th International Workshop on Intelligent Computing in Engineering. http://ceur-ws.org/Vol-2394/paper08.pdf



10:48 - 11:06

Application of MyBEM, a BIM to BEM platform, to a building renovation concept with solar harvesting technologies

Mathias Bouquerel1, Kevin Ruben Deutz1, Benoît Charrier1, Thierry Duforestel1, Mickael Rousset1, Bart Erich2, Gerrit-Jan van Riessen3, Thomas Braun4

1EDF R&D, Moret-Loing-et-Orvanne, France; 2TNO, Eindhoven, Netherlands; 3Emergo, Netherlands; 4Pilkington Germany, Gelsenkirchen, Germany

Aim and Approach

(max 200 words)

MyBEM is an innovative and modular platform designed to generate and simulate a Building Energy Model (BEM) from a Building Information Model (BIM), through an automated workflow. The platform is partly the result of the MERUBBI ANR project [1]. Building energy modelling is based on the Modelica library BuildSysPro [2].

The platform has been used to assess the energy performance of a case study within the ENVISION H2020 project [3][4]. The Envision project aims to develop and demonstrate a building renovation concept, which integrates solar harvesting technologies on the whole building envelope, including opaque and glazed parts of the vertical façades.

This case study required the development of specific models for solar harvesting elements (opaque solar collectors and PV windows), and their integration in the building energy model. The simulation of both the energy demand and the energy production can be simulated, to assess how local production can meet the energy needs.

Scientific Innovation and Relevance

(max 200 words)

The design of MyBEM is modular, in order to allow as much flexibility as possible [5]. The platform functionalities are handled by several independent modules, which communicate through file exchange. Open standards are used as much as possible for the purpose of interoperability.

A pre-processing module is able to import geometrical and construction data from various sources, and to produce a gbXML file – an extraction of BIM files dedicated to building energy modeling. This module is also able to run annual solar calculations through efficient ray tracing algorithms, so that for each façade element, solar masking and solar reflections are accurately taken into account [6].

A second module generates a building energy model in Modelica from the previously exported gbXML file. The high versatility of the Modelica library BuildSysPro is used to adapt the model to the specific needs of the Envision project study case. Indeed, Modelica models for solar harvesting technologies have been developed and integrated in the model generation algorithm.

The Modelica model is then simulated under Dymola. Post-processing routines are used to extract energy and bioclimatic indicators from the simulation.

Preliminary Results and Conclusions

(max 200 words)

The MyBEM platform has been applied to a demonstration building of the Envision project. It is a 3-storey residential building with 24 dwellings, located in the Netherlands, and built in the 1950s. The renovation configuration integrates:

- Insulation of the façades, roof and lower floor

- Change of windows

- Closure of balconies

- Integration of solar collectors on the vertical façades

- Integration of PV windows on the staircase

From a SketchUp geometric file and additional technical data, a gbXML file has been automatically generated within the pre-processing module. From this gbXML, the Modelica model has also been automatically generated.

Then simulations with Dymola have been carried out to calculate the energy needs and the energy production through solar harvesting. The coupling of both the space heating system and the solar harvesting system (based on solar collectors) is used to assess the self-consumption potential, the remaining energy needs that require an additional energy source and the unused harvested energy that can be injected in the energy networks (electrical grid or district heating network).

Main References

(max 200 words)

[1] Mathieu Schumann et al. Interdisciplinarity around design tools for new buildings and districts: the ANR MERUBBI project. Proceedings of 33rd PLEA International Conference, pages 2148-2155, Edinburgh, UK, July 2017.

[2] Gilles Plessis, Aurélie Kaemmerlen, Amy Linday. BuildSysPro: a Modelica library for modelling buildings and energy systems. Proceedings of Modelica Conference 2014, Lund, Sweden, March 2014

[3] ENVISION Project description : https://cordis.europa.eu/project/id/767180/fr

[4] Bart Erich et al. Energy harvesting by invisible solar façade collector. 14th Conference on Advanced Building Skins, Bern, Switzerland, Oct. 2019.

[5] Mathias Bouquerel, Sébastien Bermes, Adrien Brun, Hassan Bouia, Régis Lecussan, Benoît Charrier. Building Energy Modeling at District Scale through BIM Based Automatic Model Generation – Towards Building Envelope Optimization. Proceedings of Building Simulation 2019 Conference, Roma, Italy, Sept. 2019.

[6] Clément Ribault, Mathias Bouquerel, Adrien Brun, Mathieu Schumann, Gilles Rusaouen, Etienne Wurtz. Assessing tools relevance for energy simulation at the urban scale: towards decision-support tools for urban design and densification. Energy Procedia 122:871-876, September 2017



11:06 - 11:24

Optimal energy system sizing with independent load and weather time series.

François Lédée1,2, Gaëlle Faure1,2, Curran Crawford1,3, Ralph Evins1,2

1Institute for Integrated Energy Systems, University of Victoria, British Columbia, Canada; 2Energy in Cities group, Department of Civil Engineering, University of Victoria, British Columbia, Canada; 3Sustainable Systems Design Lab, Department of Mechanical Engineering, University of Victoria, British Columbia

Aim and Approach

(max 200 words)

To size an energy system with stochastic programing, hourly energy demand and weather variables over multiple years are required. Unlike weather data, hourly building’s energy demand over multiple years is usually not available. Therefore, some authors [1,2] highlight the possible use of stochastic generators. These algorithms do not jointly generate load and weather data [1,2,3], resulting in a loss of their natural correlation, possibly affecting further applications.

This study aims at assessing if an energy system sizing ran with an energy hub, an optimization framework for multi-source energy systems [4], can be conducted with independently stochastically generated time series. In this aim, we investigate if the proposed sizing for a reference simulation, where the building electric load and the solar data used are issued from the same year, differs significantly from other simulations, where the years of employed data differ. If so, we would conclude that jointly generated time series are required for multi-source energy system sizing.

We focus on the sizing of energy systems comprising a PV installation, for residential buildings in different climate zones. For each building, one year of hourly electrical load is used along with 20 different years of hourly solar data of the same location.

Scientific Innovation and Relevance

(max 200 words)

Optimization-based energy models is a growing research area aiming at supporting strategic energy planing at various scales and for different time horizons. These models require the use of time series, commonly with an hourly granularity, for example for the energy demand or the resource's availability.

Most of the commonly used models do not consider uncertainty and rely whether on past data or forecasts, often inaccurate [5]. To deal with optimization under uncertainty, two main approaches are considered: the use of robust optimization or stochastic programming. While the first “aims to find a solution with the best worst performance” [6], the second “optimizes the expected value of the objective over all possible realizations” [5].

In a multi-source energy model, the time series represent the most important parameters to consider. In an energy system, the demand and the weather conditions are often related. The current work proposes to investigate the importance of this relation in the optimization of an energy system, to see if its optimal sizing through stochastic programming can be based on the use of independent weather and building's load stochastic generators.

Preliminary Results and Conclusions

(max 200 words)

Our first results regarding a residential building in Austin (Texas, USA) reveal a undersizing of the solar facilities of 10% in average with the use of random years of sun availability, compared to the reference simulation. The sizing of other energy facilities varies between -6% and +10% and expected costs are slightly overestimated (+1.5% in average).

To assess if these differences are significantly acceptable, two analysis approaches are adopted. The first one is based on statistical tests. For a p-value of 5%, the results for the first simulated case reveals no significant difference between the reference case and other simulations for the cost and all facility size, except for the installed capacity of photovoltaic modules.

A second analysis is based on geometric approaches. Both a principal component analysis and a clustering-based analysis fail at rejecting the hypothesis of a significant overall difference between the reference simulation and other optimization sizing processes.

We will consolidate these preliminary results by multiplying the cases of study in various climate zones and for buildings with different characteristics. This would help drawing appropriates conclusions regarding the influence of the use of independent time series on the sizing of multi-source energy systems.

Main References

(max 200 words)

[1] Sun et al. (2019), Using Synthetic Traces for Robust Energy System Sizing, e-Energy 19, pp. 251-262.

[2] Sharafi M, ElMekkawy TY. Stochastic optimization of hybrid renewable energy systems using sampling average method. Renewable and Sustainable Energy Reviews. 1 déc 2015;52:1668‑79.

[3] Patidar S, Jenkins DP, Peacock A, McCallum P. Time Series decomposition for simulating electricity demand profile. In: Proceedings of Building Simulation 2019: 16th Conference of IBPSA. Rome (Italy); 2019.

[4] Evins et al. (2014), New formulations of the ‘energy hub’ model to address operational constraints. Energy 73, pp. 387–398.

[5] Moret et al (2020), Decision support for strategic energy planning: A robust optimization framework. European Journal of Operational Research 280, pp. 539-554.

[6] Moazeni et al. (2019), A Risk-Averse Stochastic Dynamic Programming Approach to Energy Hub Optimal Dispatch. IEEE Transactions on power systems 34 (3), pp. 2169-2178.



11:24 - 11:42

Evaluating the Performance of different Window Opening Styles for single-sided buoyancy-driven natural Ventilation using CFD Simulations

Akshit Gupta, Annamaria Belleri, Francesco Babich

Institute for Renewable Energy, Eurac Research, 39100 Bolzano, Italy

Aim and Approach

(max 200 words)

The aim of this research is to investigate the effectiveness of different types of windows such side-hung, top-hung, and horizontal pivot for natural and mixed-mode ventilation. This paper will focus on the CFD analysis that was performed as a preliminary step to better define the windows’ prototypes before being tested in full-scale experimental facilities.

In this study, both wind- and buoyancy-driven ventilation was considered. For both cases, the reference room included in the CFD model was one of the chambers (4m x 8m x 3m, width x depth x height) of the lab that will be later used for the tests. However, different levels of simplifications and different ways to model the boundary conditions were tests.

Firstly, the use of an external air domain was investigated to evaluate whether this was required or not, what would be its optimal size and its most appropriate boundary conditions. Secondly, different levels of geometrical simplification of the opening were compared. Thirdly, transient and steady-state simulations were performed.

For this CFD analysis, the preliminary validation of the models was based on similar previously published studies. A further and more comprehensive validation will be made after the completion of the tests with the prototypes.

Scientific Innovation and Relevance

(max 200 words)

Natural and mixed-mode ventilation (i.e. combination of natural and mechanical ventilation) are effective means to provide comfortable indoor environments (such as thermal comfort and good indoor air quality) while minimizing the energy consumption [1,2,3,4].

However, the use of different types of windows and control strategies usually lead to different indoor thermal conditions [1,5]. CFD is a powerful modelling technique to compare the air distribution within a room for varying scenarios. The boundary conditions and modelling assumptions should be carefully evaluated to ensure that the differences among the simulated scenarios are due to variations in the actual systems, and not due to other aspects such as oversimplification of the geometry or driving forces [2,4]. For instance, wind pressure coefficients are often given on the plane of the wall, but the same wind is likely to have a different indoor effect depending on the type of opening and its position (e.g. outer edge, inner edge or in the middle of a wall) [1,2,4,6].

Hence, this work aims to make a step forward by showing the effect of using different modelling assumptions and opening geometrical simplifications, in terms of results’ accuracy and required computational power.

Preliminary Results and Conclusions

(max 200 words)

In all cases, initial results indicate that, the use of an external air domain provide better results when comparing the CFD predictions with published similar studies [1,3,4].

For buoyancy-driven flows, the size of the external domain may be limited, while its boundary-conditions play an essential role. The most realistic results were achieved with an external domain as big as the testing chamber. The boundary conditions of the external domain with the top surface as opening and all the others as No-slip were most reasonable.

For wind-driven flows, the complexity increases depending on the wind direction and speed value, and on the position of the simulated room within the buildings (e.g. ground floor, mid floor, on an edge, etc.) [3,7].

Once the initial conditions are correctly defined, transient simulations usually provide the most accurate results as they can better capture the unsteady and cyclic nature of these flows, which is especially true for buoyancy-driven flows.

Lastly, the oversimplification of the geometry of walls and windows (e.g. overlooking the wall thickness, or the way in which the opened and closed sections of a window are modelled) is likely to cause unreliable results, and therefore to question the validity of the CFD analysis.

Main References

(max 200 words)

1. Wang, J., Wang, S., Zhang, T., & Battaglia, F. (2017). Assessment of single-sided natural ventilation driven by buoyancy forces through variable window configurations. Energy and buildings, 139, 762-779.

2. Cook, M. J., Ji, Y., & Hunt, G. R. (2003). CFD modelling of natural ventilation: combined wind and buoyancy forces. International Journal of Ventilation, 1(3), 169-179.

3. Gan, G. (2010). Simulation of buoyancy-driven natural ventilation of buildings—Impact of computational domain. Energy and Buildings, 42(8), 1290-1300.

4. Allocca, C., Chen, Q., & Glicksman, L. R. (2003). Design analysis of single-sided natural ventilation. Energy and buildings, 35(8), 785-795.

5. von Grabe, J., Svoboda, P., & Bäumler, A. (2014). Window ventilation efficiency in the case of buoyancy ventilation. Energy and Buildings, 72, 203-211.

6. Favarolo, P. A., & Manz, H. (2005). Temperature-driven single-sided ventilation through a large rectangular opening. Building and Environment, 40(5), 689-699.

7. Bangalee, M. Z. I., Lin, S. Y., & Miau, J. J. (2012). Wind driven natural ventilation through multiple windows of a building: A computational approach. Energy and Buildings, 45, 317-325.



11:42 - 12:00

Beyond normal: Guidelines on how to identify suitable model input distributions for building performance analysis

Giorgos Petrou1, Anna Mavrogianni2, Phil Symonds2, Mike Davies2

1UCL Energy Institute, United Kingdom; 2UCL Institute for Environmental Design and Engineering, United Kingdom

Aim and Approach

(max 200 words)

This work presents a step-by-step guide on how to identify the probability distribution function that best describes a given dataset of building-related parameters. We demonstrate the process for a set of wall U-value measurements. Firstly, histograms and cumulative distribution plots are used to visualise the data to establish whether the data appears to be normally distributed. Second, data cleaning is performed through observation of histogram extremes and removal of outliers. This is preferred over automated procedures based on the data’s interquartile range or standard deviation when the data does not appear to be normally distributed. Third, a set of candidate distributions are selected using the data’s empirical distribution and the ‘Cullen and Frey’ graph of kurtosis and square of skewness. Next, the candidate distributions are then fitted to the data using Maximum Likelihood Estimation – this is easily achieved with the R package fitdistrplus [1]. Finally, drawing from Information Theory, the Akaike Information Criterion (AIC) and its derivates are used to identify the best fitting distribution [2]. Density plots, Q-Q plots, P-P plots and Cumulative Distribution Function plots provide a supplementary measure of goodness-of-fit and inform the modeller whether the best-fitting distribution is satisfactory.

Scientific Innovation and Relevance

(max 200 words)

The importance of uncertainty propagation and model calibration in the built environment is widely recognised and distributions are an integral part of this process [3]. The normal distribution is commonly assumed in building performance simulation due its convenience and familiarity. Similarly, the uniform distribution is often used to express lack of knowledge about the possible value or distributional form of a model input. However, with data availability on the rise, distributions used for uncertainty quantification could in some cases be based on empirical evidence. If the modeller identifies the distribution that best describes the observed data relating to a model input, they can capture its expected value and shape more accurately. Alternative, the use of inappropriate distributions could contribute to the ‘performance gap’. Examples of using non-normal and non-uniform distributions exist within the field of building modelling [4, 5], however, no clear guidance on how to identify the most suitable distributions for a given dataset could be found. Therefore, by providing a detailed, step-by-step guidance of this process using code snippets in R, this paper aims to enable building performance modellers to make the best use of available data, potentially improving their modelling workflow and the accuracy of their predictions.

Preliminary Results and Conclusions

(max 200 words)

We demonstrate the step-by-step process using open source wall U-value data from English homes [6]. The data cleaning process did not reveal any outliers. Based on the empirical distribution and the Cullen and Frey graph, the candidate distributions were chosen to be the normal, Weibull, gamma and lognormal. The AIC was lowest for the gamma distribution with a value of -16.1. The difference in AIC between the best fitting distribution and the normal was 8, suggesting fairly weak support for the normal distribution to be a plausible alternative to the gamma [2]. By estimating the Akaike Weights, the probability that the gamma best describes the data amongst the candidate distributions was 0.75 while the normal had a probability of 0.01. As AIC is a relative goodness-of-fit measure, Q-Q plots, P-P plots and Cumulative Distribution Function plots were used to confirm that the gamma provides both the best fit amongst the candidate distributions and a sufficiently good fit for the given data and its intended use. To conclude, this paper shows that an alternative distribution better represents wall U-values in English homes than the more popular normal distribution. The steps taken could be followed by others to improve their modelling assumptions.

Main References

(max 200 words)

[1] Delignette-Muller ML, Dutang C. fitdistrplus: An R Package for Fitting Distributions. J Stat Softw 2015; 64: 1–34.

[2] Burnham KP, Anderson DR. Multimodel Inference: Understanding AIC and BIC in Model Selection. Sociol Methods Res 2004; 33: 261–304.

[3] Tian W, Heo Y, de Wilde P, et al. A review of uncertainty analysis in building energy assessment. Renew Sustain Energy Rev 2018; 93: 285–301.

[4] Kristensen MH, Choudhary R, Pedersen RH, et al. Bayesian Calibration Of Residential Building Clusters Using A Single Geometric Building Representation. 2017; 10.

[5] Booth AT, Choudhary R, Spiegelhalter DJ. Handling uncertainty in housing stock models. Build Environ 2012; 48: 35–47.

[6] Hulme J, Doran S. In-situ measurements of wall U-values in English housing. 290–102, Building Research Establishment (BRE) on behalf of the Department of Energy and Climate Change (DECC), 2014.

 
13:30 - 15:00Session F3.2: Ensuring high quality building simulations
Location: Cityhall (Belfry) - Room 2
Session Chair: Andreas Nicolai, TU Dresden
 
13:30 - 13:48

Analysis of the thermal inertia in historic buildings and related effects for retrofit strategies applied to urban energy modeling

Laura Carnieletto, Enrico Prataviera, Giuseppe Emmi, Michele De Carli, Angelo Zarrella

University of Padova, Italy

Aim and Approach

(max 200 words)

The retrofit of historic buildings is one of the major challenges to reduce energy use in urban city centers. In particular, Italian building stock accounts of historic buildings (i.e. older than 50 years) for more than 55%. Energy retrofit is usually complicated, due to many limitations by national laws that protect their cultural heritage or the urban assessment of the city. Therefore, few actions can improve the non-insulated high-mass envelope and the HVAC system, limiting the possibilities to reduce their energy use.

An historic building located in the city center of Padua (northern Italy) and built up in four different historic period has been investigated. The first construction belongs to XII century and the other blocks were built during the centuries, until the last part that was built during the Fascist regime. Energy Plus has been used for the detailed dynamic simulation and was compared to a Resistance-Capacitance (RC) model developed for urban building energy simulations. The RC model was applied firstly to the single parts of the building and later to the whole construction, to study the influence of thermal inertia with multiple approaches and to approach the modelling of historical buildings in urban building energy simulations.

Scientific Innovation and Relevance

(max 200 words)

Old constructions were made of massive walls and structures with high thermal inertia that can be exploited to optimize the operating condition of the system. To evaluate this effect, a Resistance-Capacitance (RC) model has been applied to each part of a historic building in the city center of Padua, which was built in 4 different periods with four different envelope structures joint together during the years. The building is mainly used for office and teaching activities, with rooms dedicated to meetings and academic ceremonies, therefore with different operating and boundary conditions during weekdays and weekends.

Results have been compared to a detailed dynamic model of the whole building implemented with the software Energy Plus, analyzing the hourly profiles. A sensitivity analysis will be performed to evaluate the effects of the input parameters, including the occupants’ presence and the operating conditions related to the different end uses. The influence of these parameters and the thermal inertia on the energy need is analysed to define more efficient strategies for historic building retrofit, taking advantage of high thermal mass and related inertia to flatten the temperature trends and optimizing systems’ operation exploiting the heat that can be stock and released by the structure.

Preliminary Results and Conclusions

(max 200 words)

The comparison between the single RC model for each construction and the overall model of the building with Energy Plus aim at evaluating the influence of massive walls and the related thermal inertia on buildings’ energy performance. This approach will be useful to model historic buildings in an urban context. Focusing on the heating and cooling profiles obtained from the simulations, optimized control strategies for heating and cooling systems can be developed, possibly reducing the operating hours, and thus the building energy use. Moreover, temperature flatten can be investigated to guarantee indoor thermal comfort of the occupants.

Furthermore, the evaluation of the thermal inertia increases the possibility of defining retrofit strategies that take advantage of this property, for example using proper insulating materials avoiding the risk of overheating due to the high thermal mass. More performing windows have been considered as building envelope refurbishment, while operating schedule modifications and preliminary sizing of a cogeneration system have been investigated for the system improvement.

This analysis can be useful to apply new strategies to groups of buildings in historic urban city centers, supporting the reduction of energy use and related CO2 emissions at wider level while respecting the existing limitations.

Main References

(max 200 words)

[1] Italian Institute of Statistic (ISTAT), Census of the Italian building stock (available at: http://dati-censimentopopolazione.istat.it, last seen 14/07/2020)

[2] Martinez-Molina A., Tort-Ausina I., Cho S., Vivancos J. L., Energy efficiency and thermal comfort in historic buildings: A review, Renewable and Sustainable Energy Reviews 61, 2016

[3] Webb A. L., Energy retrofits in historic and traditional buildings: A review of problems and methods, Renewable and Sustainable Energy Reviews 77, 2017

[4] Stazi F., Vegliò A., Di Perna C., Munafò P., Experimental comparison between 3 different traditional wall constructions and dynamic simulations to identify optimal thermal insulation strategies, Energy and Buildings 60, 2013

[5] Mancini F., Cecconi M., De Sanctis F., Beltotto A., Energy retrofit of a historic building using simplified dynamic energy modelling, 71st conference of the Italian Thermal Machine Engineering Association, ATI2016, 14-16 September 2016, Turin, Italy

[6] Caro R., Sendra J. J., Evaluation of indoor environment and energy performance of dwellings in heritage buildings. The case of hot summers in historic cities in Mediterranean Europe, Sustainable Cities and Society 52, 2020



13:48 - 14:06

Simulation of outdoor thermal comfort: a tweak with energyplus

Edouard Walther1, Carla Delmarre2, Séverine Huet1

1AREP L'hypercube, France; 2INSA Lyon, Département Génie Civil et Urbanisme, France

Aim and Approach

(max 200 words)

The aim of the present work is to provide for a simplified evaluation of surface temperatures in the outdoor built environment using an open source, state-of-the-art building energy simulation (BES) software.

A limited number of tools allow for the detailed determination of the urban micro-climate, such as the recognized ENVI-met (Bruse & Fleer, 1998) and SOLENE (Gros et al. 2014). These approaches are based on the coupling of heat transfer on built surfaces with non-isothermal fluid dynamics, their computational expense reaching days of CPU time.

At the early stage of construction projects, the available level of detail is low and iterations are often required in the design process. The aforementioned tools hence become practically unaffordable.

The work proposed here is a simplified, de-coupled approach using the open source softwares EnergyPlus and openFOAM respectively for BES and CFD. The hourly air velocity field is reconstructed from a limited number of isothermal CFD simulation similarly to (Delpech et al. 2005) and (Kastner & Dogan, 2020). The method relies on state-of-the art models for the simulation of heat transfer and fluid flow and allows for the outdoor comfort evaluation of design variants with an accessible computational effort.

Scientific Innovation and Relevance

(max 200 words)

Building energy simulation softwares are obviously able to determine the surface temperatures of external walls depending on outdoor boundary conditions, amongst which solar flux, air velocity or sky vault temperature. In order to simulate outdoor comfort, the approach used here relies in constructing thermal zones that encompass the urban environment considered, forming one “building”.

This method advantageously allows for the usage of the available features in EnergyPlus , such as the addition of shadings or the simulation of low vegetation via the green roof object. Materials of the environment are chosen depending on their constitution: building wall, roof, pavement or road surface. The computational expense is reduced as a few hours only are required for a yearly simulation of the surface temperature for the BES part. The isothermal CFD computations may run independently overnight.

Latent heat transfer to the ambiance from ponds, lawns or trees is not accounted for. However, as far as vegetation is concerned, the shading effect was proved to be the leading contributor to cooling rather than water evaporation (Morakinyo et al. 2020), (Tsoka et al. 2018). Trees are hence integrated as mere shading objects.

Preliminary Results and Conclusions

(max 200 words)

The results obtained exhibit a satisfactory behaviour compared to the experimental and numerical literature:

- The phenomenon is well reproduced in terms of dynamics and amplitude of the surface temperatures compared to (Musy et al. 2014)

- Reflexion is taken into account and visible between buildings and ground, influenced by the albedo of each surface, similarly to (Musy et al. 2014). Specular reflection of the solar flux on glazed facades is also represented.

- The shading from the buildings and the trees is correctly represented. The buildings are completely opaque whereas the trees transmit 20-30% of the solar flux to the soil (Toudert & Mayer 2005).

- The radiative flux decreases with the sky-view factor . Therefore, the radiant flux is inhibited in presence of trees, in narrow streets or close to buildings. Similar results can be observed in (Musy et al. 2014).

- The heat storage in environment's surfaces (walls, roofs, ground) is modelled with EnergyPlus' integrated wall model .

As a perspective, the calculation of local heat transfer coefficients using the air velocity fields is currently implemented. The integration of detailed view factors, following the recent evolution of energyplus is also examined (Luo et al. 2020).

Main References

(max 200 words)

Bruse M, Fleer H. Simulating surface–plant–air interactions inside urban environments with a three dimensional numerical model. Environmental modelling & software. 1998.

Kastner P, Dogan T. A cylindrical meshing methodology for annual urban computational fluid dynamics simulations. Journal of Building Performance Simulation. 2020.

Morakinyo TE, Ouyang W, Lau KK, Ren C, Ng E. Right tree, right place (urban canyon): Tree species selection approach for optimum urban heat mitigation-development and evaluation. Science of The Total Environment. 2020.

Delpech P., et al. 2005. Pedestrian wind comfort assessment criteria: A comparative Study. EACWE4. Prague: J. Naprestek & C. Fischer.

Luo X, Hong T, Tang YH. Modeling Thermal Interactions between Buildings in an Urban Context. Energies. 2020.

DoE US. EnergyPlus engineering reference. LBNL. 2009.

Musy M et al. Impact of vegetation on urban climate, thermal comfort and building energy consumption–Overview of VegDUD project results. InIC2UHI 2014 .

Toudert A, Mayer H. Thermal comfort in urban streets with trees under hot summer conditions. PLEA 2005–Passive and Low Energy Architecture, 2005, Beirut. Proceedings. 2005.

Tsoka S, Tsikaloudaki A, Theodosiou T. Analyzing the ENVI-met microclimate model’s performance and assessing cool materials and urban vegetation applications–A review. Sustainable cities and society. 2018.



14:06 - 14:24

Lumped-capacitance models to evaluate the urban cooling energy consumptions: analysis on a case-study district in the University of Padua.

Enrico Prataviera, Pierdonato Romano, Laura Carnieletto, Jacopo Vivian, Angelo Zarrella

University of Padua, Italy

Aim and Approach

(max 200 words)

In the last decade, the research in buildings physics has focused on the extension from standard building simulation tools to Urban Building Energy Modelling (UBEM) which is a wider and novel research topic aiming at the modelling of buildings in cities and urban environments. In the next future, cities’ population will grow up exponentially, increasing primary energy consumptions and global warming emissions connected to urban areas. In this perspective, several new software and platforms have been developed by research groups worldwide, trying to propose modelling solutions to the challenging issues that arise in urban environments.

Energy consumption in cooling season is becoming more and more relevant due to the increasing user requests and solar heat gains, causing temperature rise and affecting chillers’ efficiencies itself. The present paper proposes a detailed analysis on the cooling energy consumptions of a district of 9 buildings within the University campus located in Padua, northern Italy, utilizing a new UBEM platform (named EUReCA) developed by the Authors. Particular attention was also given to possible actions to reduce energy consumption and gas emission for the cooling season in a district scale perspective.

Scientific Innovation and Relevance

(max 200 words)

The proposed model, EUReCA, Energy Urban Resistance Capacitance Approach, consists of Python based tool to predict energy demand and consumption in district and city scale applications. Semantic georeferenced data and archetypes’ databases are used to derive buildings Resistance-Capacitance thermal networks (based on both one and two thermal capacitances), thus solving the thermal zone balance. Moreover, latent thermal zone balance and plants components’ models are included.

The present work is divided into two phases. Firstly a detailed analysis of the model results is proposed, comparing hourly temperature and humidity profiles to the detailed simulations carried out in EnergyPlus, used as benchmark, in all 9 buildings. Hourly and seasonal cooling demand are verified as well, and attention has been paid to the peak load difference. Secondly, the effect of several retrofit actions is discussed and compared to the actual system, which consists of a district cooling network with centralized chillers coupled to cooling towers. Envelope actions (e.g. windows substitution, low absorptance roofs and external walls) and plant actions (latent and sensible heat air handling unit recovery, night free cooling and new reversible heat pump systems) are considered and compared in a consumption reduction perspective.

Preliminary Results and Conclusions

(max 200 words)

Several simulation parameters and results were compared to the single building detailed simulation in EnergyPlus. The testing procedure has been carried out with different calculation methods, one or two thermal capacitances model considering also the effect of the climate. Results display a good prediction on the monthly and seasonal demand for both thermal networks. Hourly temperature is in good agreement for the entire district of buildings, but the zone relative humidity prediction can be inaccurate because of EUReCA’s simplified thermal zoning. The model based on two thermal capacitances presents a better performance when power peak load evaluation is considered.

Several improvements have been then modelled using EUReCA. Reducing the windows solar gain appears to be a valuable choice to reduce cooling demand, while, on the plant side, consumptions benefits from a night free cooling solution. The substitution of the cooling towers with a ground source heat pump could strongly decrease energy consumptions, although their installation involves a high initial cost and technical issues related to the available space.

Main References

(max 200 words)

T. Hong, Y. Chen, X. Luo, N. Luo, and S. H. Lee, “Ten questions on urban building energy modeling,” Build. Environ., vol. 168, p. 106508, Jan. 2020.

United Nations Department of Economic and Social Affairs, “Revision of World Urbanization Prospects,” 2018.

A. Sola, C. Corchero, J. Salom, and M. Sanmarti, “Multi-domain urban-scale energy modelling tools: A review,” Sustain. Cities Soc., p. 101872, Oct. 2019.

International Organization for Standardization, “ISO 13790:2008 Energy performance of buildings — Calculation of energy use for space heating and cooling,” 2008.

German Association of Engineers, “Calculation of transient thermal response of rooms and buildings - modelling of rooms (VDI 6007-1),” 2012.



14:24 - 14:42

GIS-based multi-scale residential building energy modeling using a data-driven approach

Usman Ali1, Mohammad Haris Shamsi1, Mark Bohacek3, Karl Purcell3, Cathal Hoare1, Eleni Mangina2, James O’Donnell1

1School of Mechanical & Materials Engineering, Energy Institute University College Dublin (UCD), Ireland; 2School of Computer Science and Informatics, University College Dublin (UCD), Ireland; 3Sustainable Energy Authority Of Ireland, Dublin, Ireland

Aim and Approach

(max 200 words)

In order to adapt to climate change, urban planning and development strategies are undergoing a transformation from conventional design to more innovative approaches. As such, city planners often develop strategic sustainable energy plans to minimize overall energy consumption and CO2 emissions. Planning at such scales could be informed by the spatial analysis of building stock using Geographic Information Systems (GIS) based mapping. Generally, the building stock is available in the form of building Energy Performance Certificates (EPC) database that provides an indication of buildings' energy use and carbon emission predictions and can play an important role in energy and climate policymaking. The creation of an EPC for any individual building requires extensive information surveys. Hence these ratings typically only exist for a subset of the entire building stock. A data-driven methodology could aid in the identification of building energy performance using existing available building data.

Scientific Innovation and Relevance

(max 200 words)

This research proposes a novel generalizable methodology for data-driven GIS-based residential building energy modeling at multiple scales. Different machine learning algorithms are examined to predict building energy ratings for GIS-based multi-scale mapping.

Preliminary Results and Conclusions

(max 200 words)

This paper develops a methodology for GIS-based residential building energy modeling at a multi-scale using a data-driven approach. The machine-learning algorithm predicts building energy ratings from local to national scale using the bottom-up approach. The predictive modeling results are coupled with GIS for multi-scale mapping. The methodology is applied to Irish residential building stock and the energy rating is examined at multiple scales. The modeling results indicate priority geographical areas that have the greatest potential for energy savings.

Main References

(max 200 words)

Wei, Y., X. Zhang, Y. Shi, L. Xia, S. Pan, J. Wu,M. Han, and X. Zhao (2018). A review of data-driven approaches for prediction and classificationof building energy consumption.Renewable andSustainable Energy Reviews 82, 1027–1047.

Amasyali, K. and N. M. El-Gohary (2018). A re-view of data-driven building energy consumptionprediction studies.Renewable and Sustainable En-ergy Reviews 81, 1192–1205.

Y. Sun, F. Haghighat, B. C. Fung, A review of the-state-of-the-art in data-driven approaches forbuilding energy prediction, Energy and Buildings (2020) 110022.

 
15:00 - 16:30Session F4.2: Ensuring high quality building simulations
Location: Cityhall (Belfry) - Room 2
Session Chair: Nils Artiges, Univ. Grenoble Alpes, CNRS, Grenoble INP, G2Elab, F-38000 Grenoble, France
Session Chair: Lien De Backer, Ghent University
 
15:00 - 15:18

Carbon-cost efficient retrofit of passive and active systems in residential buildings using genetic algorithm

Negar Mohtashami1,2, Rita Streblow1, Linda Hildebrand2, Dirk Müller1

1Institute for Energy Efficient Buildings and Indoor Climate, RWTH Aachen University, Germany; 2Chair of Reuse in Architecture, Faculty of Architecture, RWTH Aachen University, Germany

Aim and Approach

(max 200 words)

In the past two decades, improving the energy performance of existing buildings is a major trend to reduce the environmental impacts since existing buildings make up for the largest share compared to new buildings. The energy consumed in a building consists of both embodied and operational form. However, most current conducted energy optimizations only consider operational energy and remain reluctant to the embodied energy invested in building materials and services during the life cycle of a building. This study addresses both types of energy together and considers building as a whole in order to optimize properties of the building envelope and HVAC systems simultaneously.

Scientific Innovation and Relevance

(max 200 words)

The current research uses MOGA (Multi Objective Genetic Algorithm) to minimize CO2 equivalent emissions, and costs in order to find optimal retrofit scenarios for a typical multi-family house (MFH06) according to TABULA building classification for Germany.

Preliminary Results and Conclusions

(max 200 words)

Findings show four clusters of refurbishment scenarios that are mainly categorized based on the amount of insulation materials. it is also perceived that the most optimal carbon-cost retrofit options focus on increasing the thermal energy storage capacity and remain reluctant in insulating the envelope or changing the windows for a typical multi-family house of 70s mainly due to high embodied energy in the insulation materials and devices.

Main References

(max 200 words)

Evins R. A review of computational optimisation methods applied to sustainable building design. Renewable and Sustainable Energy Reviews 2013; 22: 230–45.

Ramesh, T., Prakash, R., & Shukla, K. K. (2010). Life cycle energy analysis of buildings: An overview. Energy and buildings, 42(10), 1592-1600.

Verbeeck G, Hens H. Life Cycle Optimization of Extremely Low Energy Dwellings. Journal of Building Physics 2007; 31(2): 143–77.

Vilches, A., Garcia-Martinez, A., & Sanchez-Montanes, B. (2017). Life cycle assessment (LCA) of building refurbishment: A literature review. Energy and Buildings, 135, 286-301.



15:18 - 15:36

Application of a long-term MPC formulation to hybrid GEOTABS buildings

Iago Cupeiro Figueroa1, Lieve Helsen1,2

1KU Leuven, Belgium; 2Energyville, Belgium

Aim and Approach

(max 200 words)

This research evaluates the benefits of applying a long-term model predictive control (MPC) formulation to hybrid GEOTABS buildings [1], which consist of a ground-source heat pump (GSHP) and a thermally activated building system (TABS) emission system to cover most of the building energy needs, and a secondary but fast-reacting system to assist the primary system during peak periods. To that end, the methodology presented at [2] is applied to a generic modular hybrid GEOTABS building simulation model for different building balance degrees (i.e., heating or cooling dominated), electricity-gas price ratios and borefield sizes. The possibility of active regeneration is also analyzed.

Scientific Innovation and Relevance

(max 200 words)

To ensure an optimal coordination between the components of a hybrid GEOTABS system an MPC methodology can be applied, reducing the energy use and increasing the cost savings of the building while keeping or even improving the indoor comfort [3]. However, MPCs typically optimize the control actions for an horizon that foresights a few days, while the geothermal borefield dynamics last for several years [4]. The contribution of this research is to evaluate in which situations it is beneficial to apply a long-term formulation that foresights a full year of operation. For example, in the case of passive cooling, is it more beneficial to use it as early during the summer season as possible or to save its capacity towards the end of the season?

Preliminary Results and Conclusions

(max 200 words)

A modular model that comprises a typical hybrid GEOTABS configuration is constructed using Modelica. An MPC optimization problem is constructed using TACO [5], which allows the translation and compilation of non-linear problems (NLPs) using Optimica and in a similar fashion as JModelica. The set of models is simulated for a period of 5 years.

Main References

(max 200 words)

[1] Himpe, E., Vercautere, M., Boydens, W., Helsen, L., & Laverge, J. (2018). GEOTABS concept and design: state-of-the-art, challenges and solutions. In REHVA Annual Meeting Conference Low Carbon Technologies in HVAC.

[2]Cupeiro Figueroa, I., Cimmino M., Helsen L. A methodology for Long-term Model Predictive Control of hybrid geothermal systems: theshadow-cost formulation. Under review

[3]Cupeiro Figueroa, I., Cigler, J., & Helsen, L. (2018). Model Predictive control formulation: a review with focus on hybrid geotabs buildings. In https://www. rehvam2018atic. eu/images/workshops/9/Figuereroa. pdf (pp. 1-9). Proceedings of the REHVA Annual Meeting Conference.

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

[5] Jorissen, F., Boydens, W., & Helsen, L. (2019). TACO, an automated toolchain for model predictive control of building systems: implementation and verification. Journal of Building Performance Simulation, 12(2), 180-192.



15:36 - 15:54

Development and validation of radiation-coupled multimodal heat flux boundary condition for incompressible buoyant internal flows in OpenFOAM

Jake Haskell1, Mike Jäger1, Pia Riedel1, Jerell Gill2, Paul Lynch2, Talbot Kingsbury2, Steven Downie2

1Arup, Advanced Building Engineering, Germany; 2Arup, Advanced Digital Engineering, UK

Aim and Approach

(max 200 words)

The open-source CFD code OpenFOAM has been gaining relevance for the investigation of internal flow phenomena for building physics applications over the course of the past decade, but a major limitation to more widespread adoption has the necessity to use more computationally expensive compressible models to effectively calculate the effects of heat transfer. Furthermore radiation coupling with the default boundary conditions is limited at best and poorly documented to date. Most internal flows can be accurately modelled using the Boussinesq approach and more computationally efficient incompressible solvers, however the adequate thermal boundary conditions are not yet implemented for the OpenFOAM incompressible buoyant solvers and the existing compressible thermal boundary conditions are ill-suited for building physics applications. A new thermal boundary condition is developed to close this gap to allow more accurate CFD modelling of thermally driven buoyant internal flows using OpenFOAM.

Scientific Innovation and Relevance

(max 200 words)

This study documents the development and validation of a new thermal boundary condition that offers the user the ability effectively calculate specific and absolute wall heat fluxes as well as the heat flux resulting from the definition of an external temperature and wall thermal resistance. This new boudary condition allows improved CFD approximation of thermally internal flow for building applications and has furthermore been coupled with the DOM and view factor radiation models to further improve the quality of heat transfer modelling using CFD.

Preliminary Results and Conclusions

(max 200 words)

The new boundary condition is developed in C++ first without radiation coupling and tested to ensure adequate calcuation of a heat flux for the three different modes. Following successful implementation and error testing, the boundary condition is tested on a simple L-shaped room case and benchmarked for accuracy against ANSYS CFX. The radiation coupling is then integrated and the boundary condition is verified against the analog case calculated in CFD; the results show very good agreement for air, surface and mean radiant temperatures. Six different parameter configurations using the boundary condition are investigated and the results show maximum deviation of 0.2°C between the two simulation models. The DOM model shows slightly better agreement with regard to the radiation modelling compared the view factors model.

Main References

(max 200 words)

Cid, K. 2016. A Comparative study between thermal radiation models P1 and discrete ordinates using CFD software OpenFOAM, Congresso Internacional de Fluidodinâmica Computacional

Frie, F. 2014. Calculation of radiative losses of solar receivers using viewfactors, OpenFOAM User Conference 2014

Junior et al. 2016. Numerical validation of viewFactor and FVDOM radiation models of OpenFOAM® and application. Revista chilena de ingeria 26, S. 546-556.

Haskell et al. 1994.Boundary Conditions for the Diffusion Equation in

Radiative Transfer. Journal of Optical Society of America 10. S. 2727-2740

Koncar, B. and Koncar L. 2018. Open access peer-reviewed chapter

Use of CFD Codes for Calculation of Radiation Heat Transfer: From Validation to Application. In: Heat Transfer: Models, Methods and Applications. Kingston University London.

Modest, M. 2013. Radiative Heat Transfer, 3rd Edition. Academic Press

Programmers Guide, OpenFOAM v1806, 2018

Vdovin, A. 2009. Radiative Heat Transfer in OpenFOAM, Chalmers University of Technology



15:54 - 16:12

Optimal control of TABS by Sparse MPC

Yasuyuki Shiraishi1, Masaaki Nagahara1, Dirk Saelens2

1The University of Kitakyushu, Japan; 2KU Leuven, Belgium

Aim and Approach

(max 200 words)

In this study, continuous energy use of Thermally Activated Building System (TABS) is minimized by the sparse optimal control that combines MPC and sparse modeling in order to improve the unsteady actual operation performance of TABS. In other words, we propose a method to improve unsteady energy saving performance of TABS and durability of air conditioning equipment. Furthermore, the purpose of this study is to clarify the energy-saving performance and the control performance of indoor environment by introducing the proposed method to TABS based on numerical simulation.

In this analysis, the effectiveness of the proposed method is verified by using a coupled analysis tool [1] of unsteady CFD analysis and MTLAB/Simulink for a general office space with TABS. Specifically, the water flow rate of TABS has been optimized by the combined method of MPC and sparse modeling so that the ceiling surface temperature of TABS reaches the target value is given as an input condition for CFD analysis. The effectiveness of the proposed method is verified through evaluation of control performance and energy saving performance.

As a case study, we will analyze the results of two cases: normal MPC control (Case1) and combined control of MPC and sparse modeling (Case2).

Scientific Innovation and Relevance

(max 200 words)

TABS, which utilizes the building structure to emit and store energy, is becoming increasingly popular. So far, the introduction of TABS has been progressing mainly in Europe [2], but in recent years, the introduction has also been attempted in Japan [3].

As shown in previous studies [2], TABS is expected to have various advantages such as peak shift, reduction of heat source capacity, and cost reduction by utilizing large heat capacity in addition to energy saving and comfort. On the other hand, since the thermal response is slow due to the large heat capacity, control for creating a comfortable indoor thermal environment is important.

For this reason, study on Model Predictive Control (MPC) [4] that determines the current manipulated variable while predicting the behavior of the controlled variable has attracted attention as a new control method that replaces classical control for the operation of TABS. Furthermore, by combining this MPC and sparse modeling [5], it is possible to realize further energy savings while maintaining control performance and improve durability by minimizing the start and stop frequency of air conditioning equipment. However, application of this method to engineering problems has not been reported.

Preliminary Results and Conclusions

(max 200 words)

In both cases, by using MPC, the TABS is activated before the heat load occurs. As a result, the control error of the ceiling surface temperature was reduced throughout the analysis period, and the average control error on each day was less than 0.3℃.

Preliminary results showed that, in Case1, water was often delivered at a low flow rate of 0.5 L/min. On the other hand, in Case2, compared with Case1, the operating time for 5 days on weekdays was reduced by about 14 hours in total. Therefore, the sparseness of the water flow rate (expansion of the time zone when the water flow rate became zero) was confirmed by using both MPC and sparse modeling. Regarding cumulative water flow rate, in Case2, it was possible to reduce by approximately 39% over the entire analysis period compared with Case1.

By controlling the ceiling temperature, the PMV values in the workspace satisfy the comfort zone in both cases, and the distribution in the horizontal plane was extremely small.

From the above, it has been confirmed that by combining MPC and sparse modeling, it is possible to achieve sparseness of the operation amount while satisfying comfort in the workspace.

Main References

(max 200 words)

[1] Y. Ogawa, Y. Shiraishi, Multi-Objective Optimization of Energy Saving and Thermal Comfort in Thermo Active Building System based on Model Predictive Control, 40th AIVC conference Ghent, Belgium, 2019

[2] D. Olsthoorn, F. Haghighat, A. Moreau, and G. Lacroix, Abilities and limitations of thermal mass activation for thermal comfort, peak shifting and shaving: A review, Building and Environment, VoL.118, pp.113-127, 2017

[3] E. Kataoka, Y. Shiraishi, et al., Radiation Cooling and Heating using Building Thermal Storage for Outside Insulation Building -Part 1. The Architectural Summary of the Building and Equipment System and the Report of Piece Model Experiment Result-, SHASE (The Society of Heating, Air-Conditioning and Sanitary Engineers) of Japan, J-30, pp.317-320, 2016(in Japanese)

[4] A. Afram, and F. Janabi-Sharif, Theory and applications of HVAC control systems – A review of model predictive control (MPC), Building and Environment, VoL.72, 2014

[5] M. Nagahara et al.: Maximum hands-off control - a paradigm of control effort minimization-, IEEE Trans. Automatic Control, 61(3), pp.735-747, 2016



16:12 - 16:30

Developing an archetype building stock model for new cities in Egypt

Fady Abdelaziz, Rokia Raslan, Phil Symonds

UCL Institute for Environmental Design and Engineering

Aim and Approach

(max 200 words)

Egypt’s growing population in the last few decades has led to a significant rise in housing demands. This directed the government to initiate a national project with the goal of developing 50 new satellite cities in the arid desert by 2030 to mitigate the high population density in major cities such as Cairo and Giza. The Egyptian building stock comprises around 13.5 million residential buildings, with almost 37 million residential units. More than 50% of these buildings were built in the last two decades. This has resulted in the residential sector accounting for 47% of total electrical energy consumption in Egypt, as well as 5% of the total CO2 emissions. Developing a residential building stock model, based on representative archetypes presents a strong potential for understanding and analyzing the overall energy performance of the stock. In addition, it allows the prediction of future energy demand and CO2 emissions. Existing data in Egypt provides an overview of the most common archetypes of building stock in terms of building height, construction method, and year of construction, however, these databases lack crucial information regarding the building's physical data that can be used in evaluating energy performance.

Scientific Innovation and Relevance

(max 200 words)

This paper presents the development of ENCEM (Egyptian New Cities Energy Model), which is based on a bottom-up model of building stock archetypes for the new cities within the Greater Cairo region. The study develops the framework of the archetypes using data from 201,440 domestic buildings sampled from 9 new city districts that were constructed in Cairo and Giza governorates over the last 30 years. The study is built on data from CAPMAS (Central Agency for Public Mobilization and Statistics) Egyptian Housing Survey and Census. The energy simulation software tool, EnergyPlus is employed in developing this model to generate an hourly energy demand profile for each archetype. This study will provide a more accurate representation of the overall building stock variability in terms of building type, geometric form, building envelope, and overall energy consumption.

Preliminary Results and Conclusions

(max 200 words)

From a bottom-up approach, the resulting model can be generalized to other cities with similar climates and can be studied further to develop a national building stock for Egypt. Developing this model will act as a key tool for governmental decision-makers and stakeholders in Egypt to be informed with the energy use and the energy-saving potential of the building stock, and will also help policy developers and building scientists to identify replacement or retrofit measures for the various categories of Egypt’s housing archetypes. Understanding these measures will not only reflect on existing building stock but will also provide guidelines for the government’s building codes and legislation to be implemented in new constructions.

Main References

(max 200 words)

- Kavgic, M., Mavrogianni, A., Mumovic, D., Summerfield, A., Stevanovic, Z., & Djurovic-Petrovic, M. (2010). A review of bottom-up building stock models for energy consumption in the residential sector. Building And Environment, 45(7), 1683-1697. doi: 10.1016/j.buildenv.2010.01.021

- Pasichnyi, O., Wallin, J., & Kordas, O. (2019). Data-driven building archetypes for urban building energy modelling. Energy, 181, 360-377. doi: 10.1016/j.energy.2019.04.197

- Famuyibo, A., Duffy, A., & Strachan, P. (2012). Developing archetypes for domestic dwellings—An Irish case study. Energy And Buildings, 50, 150-157. doi: 10.1016/j.enbuild.2012.03.033

- Krarti, M., Aldubyan, M., & Williams, E. (2020). Residential building stock model for evaluating energy retrofit programs in Saudi Arabia. Energy, 195, 116980. doi: 10.1016/j.energy.2020.116980

 

 
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