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, 14:34:11 CEST

Session Overview
Session F3.2: Ensuring high quality building simulations
Friday, 03/Sept/2021:
13:30 - 15:00

Session Chair: Andreas Nicolai, TU Dresden
Location: Cityhall (Belfry) - Room 2

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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:, 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.

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