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Research Article

On the impact of local microclimate on building performance simulation. Part I: Prediction of building external conditions

Lucie Merlier1,2( )Loïc Frayssinet1,2Kévyn Johannes1,2Frédéric Kuznik1,2
Univ Lyon, CNRS, INSA-Lyon, Université Claude Bernard Lyon 1, CETHIL UMR5008, F-69621, Villeurbanne, France
BHEE: High Energy Efficiency Buildings, joint laboratory CETHIL / EDF, France
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Abstract

To better predict the effective energy performance of buildings in cities, this study addresses the modelling of local external radiative, thermal and aeraulic conditions. After reviewing existing modelling approaches that are suitable for estimating the building boundary conditions in energy simulation, this paper analyses external conditions derived from a building energy model (BuildSysPro) or a microclimatic model (SOLENE microclimat). Comparisons are made for the different faces of a generic building standing alone or located in an urban environment, with or without a thermally efficient envelope. When the modelling approach is adjusted, the results highlight significant deviations on the estimated radiative temperatures and wind-based quantities around the isolated building. When accounting for surrounding buildings, the results show a substantial reduction in short-wave radiative fluxes, which is explained by an imbalance between solar masks and multireflections, and a reduction in the wind-driven ventilation potential.

References

 
J Allegrini, V Dorer, J Carmeliet (2012). Influence of the urban microclimate in street canyons on the energy demand for space cooling and heating of buildings. Energy and Buildings, 55: 823-832.
 
J Allegrini, JH Kämpf, V Dorer, J Carmeliet (2013). Modelling the urban microclimate and its influence on building energy demands of an urban neighbourhood. In: Proceedings of CISBAT 2013 Cleantech for Smart Cities and Buildings. Vol. 2. EPFL Solar Energy and Building Physics Laboratory (LESO-PB), pp. 867-872.
 
J Allegrini, K Orehounig, G Mavromatidis, F Ruesch, V Dorer, R Evins (2015). A review of modelling approaches and tools for the simulation of district-scale energy systems. Renewable and Sustainable Energy Reviews, 52: 1391-1404.
 
B Blocken (2015). Computational Fluid Dynamics for urban physics: Importance, scales, possibilities, limitations and ten tips and tricks towards accurate and reliable simulations. Building and Environment, 91: 219-245.
 
S Bontemps, A Kaemmerlen, G Blatman, L Mora (2013). Reliability of dynamic simulation models for building energy in the context of low-energy buildings. In: Proceedings of the 13th International IBPSA Building Simulation Conference, Chambéry, France.
 
S Bontemps, L Mora, M Schumann (2016). Validation expérimentale appliquée à la modélisation d’une cellule test de type basse consommation. In: Proceedings of the IBPSA France Conference, Marne-la-Vallée, France.
 
J Bouyer, C Inard, M Musy (2011). Microclimatic coupling as a solution to improve building energy simulation in an urban context. Energy and Buildings, 43: 1549-1559.
 
E Bozonnet (2006). Les microclimats urbains et la demande énergétique du bâti. In: Proceedings of 24èmes Rencontres Universitaires de Génie Civil. (in French)
 
E Bozonnet, M Musy, I Calmet, F Rodriguez (2015). Modeling methods to assess urban fluxes and heat island mitigation measures from street to city scale. International Journal of Low-Carbon Technologies, 10: 62-77.
 
M Bruse (2004). Envi-met 3.0: Updated Model Overview. Available at http://envi-met.net/documents/papers/overview30.pdf
 
B Bueno, L Norford, J Hidalgo, G Pigeon (2013). The urban weather generator. Journal of Building Performance Simulation, 6: 269-281.
 
BuildSysPro (2018). Documentation, EDF R & D.
 
H Chen, R Ooka, K Harayama, S Kato, X Li (2004). Study on outdoor thermal environment of apartment block in Shenzhen, China with coupled simulation of convection, radiation and conduction. Energy and Buildings, 36: 1247-1258.
 
J Clarke (2007). Energy Simulation in Building Design. Abingdon, UK: Routledge.
 
CNRM-UMR (2018). CNRM-UMR 3589. Town Energy Balance website. Available at https://www.umr-cnrm.fr/spip.php?article199
 
D Cóstola, B Blocken, JLM Hensen (2009). Overview of pressure coefficient data in building energy simulation and airflow network programs. Building and Environment, 44: 2027-2036.
 
CSTB (2012). RT2012: Règles Th-U, fascicule 4 : Parois opaques.
 
FS de la Flor, SA Domínguez (2004). Modelling microclimate in urban environments and assessing its influence on the performance of surrounding buildings. Energy and Buildings, 36: 403-413.
 
EnergyPlus (2018). Documentation, U.S. Department of Energy.
 
J Franke (2006). Recommendations of the COST action C14 on the use of CFD in predicting pedestrian wind environment. In: Proceedings of the 4th International Symposium on Computational Wind Engineering, Yokohama, Japan, pp. 529-532.
 
L Frayssinet, L Merlier, F Kuznik, J-L Hubert, M Milliez, J-J Roux (2017). Modeling the heating and cooling energy demand of urban buildings at city scale. Renewable and Sustainable Energy Reviews, 81: 2318-2327.
 
C Ghiaus, F Allard, M Santamouris, C Georgakis, F Nicol (2006). Urban environment influence on natural ventilation potential. Building and Environment, 41: 395-406.
 
J Goffart (2016). Données d’entrée: climat. In: Energétique des bâtiments et simulation thermique. Blanche BTP. Eyrolles, pp. 231-240.
 
A Gros, E Bozonnet, C Inard, M Musy (2016). Simulation tools to assess microclimate and building energy: A case study on the design of a new district. Energy and Buildings, 114: 112-122.
 
J Jokisalo, J Kurnitski, M Korpi, T Kalamees, J Vinha (2009). Building leakage, infiltration, and energy performance analyses for Finnish detached houses. Building and Environment, 44: 377-387.
 
J Le Bras, V Masson (2015). A fast and spatialized urban weather generator for long-term urban studies at the city-scale. Frontiers in Earth Science, 3: 27.
 
A Lemonsu, CSB Grimmond, V Masson (2004). Modeling the surface energy balance of the core of an old mediterranean city: Marseille. Journal of Applied Meteorology, 43: 312-327.
 
L Malys, M Musy, C Inard (2015). Microclimate and building energy consumption: Study of different coupling methods. Advances in Building Energy Research, 9: 151-174.
 
V Masson (2000). A physically-based scheme for the urban energy budget in atmospheric models. Boundary-Layer Meteorology, 94: 357-397.
 
V Masson, C Marchadier, L Adolphe, R Aguejdad, P Avner, M Bonhomme, G Bretagne, X Briottet, B Bueno, C de Munck, et al. (2014). Adapting cities to climate change: A systemic modelling approach. Urban Climate, 10: 407-429.
 
L Merlier, F Kuznik, G Rusaouën, S Salat (2018). Derivation of generic typologies for microscale urban airflow studies. Sustainable Cities and Society, 36: 71-80.
 
L Merlier, L Frayssinet, K Johannes, F Kuznik (2019). On the impact of local microclimate on building performance simulation. Part II: Effect of external conditions on the dynamic thermal behavior of buildings. Building Simulation, .
 
Météo France (2017). Météo et climat : données climatiques de la station de lyon.
 
M Mirsadeghi, D Cóstola, B Blocken, JLM Hensen (2013). Review of external convective heat transfer coefficient models in building energy simulation programs: Implementation and uncertainty. Applied Thermal Engineering, 56: 134-151.
 
P Moonen, T Defraeye, V Dorer, B Blocken, J Carmeliet (2012). Urban Physics: Effect of the micro-climate on comfort, health and energy demand. Frontiers of Architectural Research, 1: 197-228.
 
B Morille, N Lauzet, M Musy (2015). SOLENE-microclimate: A tool to evaluate envelopes efficiency on energy consumption at district scale. Energy Procedia, 78: 1165-1170.
 
Musy M, Bozonnet E (2016). Données d’entrée: Microclimat et environnement proche. In: Energétique des bâtiments et simulation thermique. Blanche BTP. Eyrolles, pp. 240-256.
 
M Musy, I Calmet, E Bozonnet, F Rodriguez (2012). Modélisation des interactions ville climat energie. Références Modélisation urbaine: de la représentation au projet, 16-33.
 
M Musy, L Malys, B Morille, C Inard (2015). The use of SOLENE-microclimat model to assess adaptation strategies at the district scale. Urban Climate, 14: 213-223.
 
M Nunez, TR Oke (1977). The energy balance of an urban canyon. Journal of Applied Meteorology, 16: 11-19.
 
TR Oke (1982). The energetic basis of the urban heat island. Quarterly Journal of the Royal Meteorological Society, 108(455): 1-24.
 
TR Oke (2002). Boundary Layer Climates, 2nd edn. Abingdon, UK: Routlege.
 
Penicaud H (2016). Introduction. In: Energétique des bâtiments et simulation thermique. Blanche BTP. Eyrolles. pp. 17-21.
 
G Pigeon, K Zibouche, B Bueno, J Le Bras, V Masson (2014). Improving the capabilities of the Town Energy Balance model with up-to-date building energy simulation algorithms: An application to a set of representative buildings in Paris. Energy and Buildings, 76: 1-14.
 
G Plessis, A Kaemmerlen, A Lindsay (2014). BuildSysPro: A Modelica library for modelling buildings and energy systems. In: Proceedings of the 10th International Modelica Conference, Lund, Sweden, pp. 1161-1169.
 
R Ramponi, I Gaetani, A Angelotti (2014). Influence of the urban environment on the effectiveness of natural night-ventilation of an office building. Energy and Buildings, 78: 25-34.
 
D Robinson, F Haldi, J Kämpf, P Leroux, D Perez, A Rasheed, U Wilke (2009). CitySim: Comprehensive micro-simulation of resource flows for sustainable urban planning. In: Proceedings of the 11th International IBPSA Building Simulation Conference, Glasgow, UK, pp. 1083-1090.
 
U Rochard, S Shanthirablan, C Brejon, M Chateau le Bras (2015). Bâtiments résidentiels: Typologie du parc existant et solutions exemplaires pour la rénovation énergétique en France. Technical Report.
 
A Rodler, S Guernouti, M Musy, J Bouyer (2018). Thermal behaviour of a building in its environment: Modelling, experimentation, and comparison. Energy and Buildings, 168: 19-34.
 
J Roux, F Kuznik (2016). Modélisation thermique du bâtiment. In: Energétique des bâtiments et simulation thermique. Blanche BTP. Eyrolles. pp. 26-43.
 
M Santamouris (2014). On the energy impact of urban heat island and global warming on buildings. Energy and Buildings, 82: 100-113.
 
M Santamouris, C Cartalis, A Synnefa, D Kolokotsa (2015). On the impact of urban heat island and global warming on the power demand and electricity consumption of buildings: A review. Energy and Buildings, 98: 119-124.
 
M Santamouris, N Papanikolaou, I Livada, I Koronakis, C Georgakis, A Argiriou, DN Assimakopoulos (2001). On the impact of urban climate on the energy consumption of buildings. Solar Energy, 70: 201-216.
 
KH Schlünzen, D Grawe, SI Bohnenstengel, I Schlüter, R Koppmann (2011). Joint modelling of obstacle induced and mesoscale changes—Current limits and challenges. Journal of Wind Engineering and Industrial Aerodynamics, 99: 217-225.
 
M Schumann, B Charrier, G Plessis, B Wall-Ribot (2016). BuildSysPro un bibliothèque Modelica open source pour l’énergétique des bâtiments et des quartiers. In: Proceedings of the IBPSA France Conference. Marne-la-Vallée, France.
 
Y Sun, Y Heo, H Xie, M Tan, J Wu, G Augenbroe (2011). Uncertainity quantification of microclimate variables in building energy simulation. In: Proceedings of the 12th International IBPSA Building Simulation Conference, Sydney, Australia, pp. 2423-2430.
 
Y Sun, G Augenbroe (2014). Urban heat island effect on energy application studies of office buildings. Energy and Buildings, 77: 171-179.
 
Y Sun, Y Heo, M Tan, H Xie, C Jeff Wu, G Augenbroe (2014). Uncertainty quantification of microclimate variables in building energy models. Journal of Building Performance Simulation, 7: 17-32.
 
Y Tominaga, A Mochida, R Yoshie, H Kataoka, T Nozu, M Yoshikawa, T Shirasawa (2008). AIJ guidelines for practical applications of CFD to pedestrian wind environment around buildings. Journal of Wind Engineering and Industrial Aerodynamics, 96: 1749-1761.
 
Y Toparlar, B Blocken, B Maiheu, GJF van Heijst (2017). A review on the CFD analysis of urban microclimate. Renewable and Sustainable Energy Reviews, 80: 1613-1640.
 
X Yang, L Zhao, M Bruse, Q Meng (2012). An integrated simulation method for building energy performance assessment in urban environments. Energy and Buildings, 54: 243-251.
 
YK Yi, N Feng (2013). Dynamic integration between building energy simulation (BES) and computational fluid dynamics (CFD) simulation for building exterior surface. Building Simulation, 6: 297-308.
Building Simulation
Pages 735-746
Cite this article:
Merlier L, Frayssinet L, Johannes K, et al. On the impact of local microclimate on building performance simulation. Part I: Prediction of building external conditions. Building Simulation, 2019, 12(5): 735-746. https://doi.org/10.1007/s12273-019-0507-7

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Received: 26 July 2018
Revised: 19 November 2018
Accepted: 19 December 2018
Published: 13 April 2019
© Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019
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