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Modeling building resilience against extreme weather by integrated CityFFD and CityBEM simulations

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  • Katal, Ali
  • Mortezazadeh, Mohammad
  • Wang, Liangzhu (Leon)

Abstract

In the past decade, urban building energy models have been developed to address the increasing concerns over energy consumption and greenhouse gas emission due to rapid urbanization and building resilience as a result of climate change. These models can estimate energy consumption, GHG emission and resilience response of buildings in an urban area, and evaluate retrofit strategies for architects, engineers, researchers and policy makers. It has been recognized that local microclimate and neighborhood effects play an important role in urban building energy modeling. Creating an urban building energy model also requires the collection of extensive building data, which is a time-consuming process. In this study, we developed an integrated platform by combining CityFFD (City Fast Fluid Dynamics), an urban-scale fast fluid dynamics model for microclimate modeling, and CityBEM (City Building Energy Model), a new urban building energy model with a library of 1700 building archetypes for facilitating urban model creation. Local aerodynamics and heat transfer information are exchanged between both models at each time step. Graphics processing unit computing is also applied to CityFFD for simulation speedup. The simulation of the 1971 Montreal snowstorm of the century was conducted as a case study of more than 1500 buildings of an island near Montreal, Canada for the investigation of their resilience against the three-day power outage due to the storm. Building retrofit analysis was also conducted to evaluate the added level of resilience. The results show that the proposed platform can produce high-resolution results of building thermal load, microclimate condition, and building behavior during weather extremes.

Suggested Citation

  • Katal, Ali & Mortezazadeh, Mohammad & Wang, Liangzhu (Leon), 2019. "Modeling building resilience against extreme weather by integrated CityFFD and CityBEM simulations," Applied Energy, Elsevier, vol. 250(C), pages 1402-1417.
  • Handle: RePEc:eee:appene:v:250:y:2019:i:c:p:1402-1417
    DOI: 10.1016/j.apenergy.2019.04.192
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    Cited by:

    1. Hong, Tianzhen & Ferrando, Martina & Luo, Xuan & Causone, Francesco, 2020. "Modeling and analysis of heat emissions from buildings to ambient air," Applied Energy, Elsevier, vol. 277(C).
    2. Oraiopoulos, A. & Howard, B., 2022. "On the accuracy of Urban Building Energy Modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    3. Azam Ghezelbash & Jay Liu & Seyed Hamed Fahimifard & Vahid Khaligh, 2024. "Exploring the Influence of the Digital Economy on Energy, Economic, and Environmental Resilience: A Multinational Study across Varied Carbon Emission Groups," Sustainability, MDPI, vol. 16(7), pages 1-22, April.
    4. Wang, Chong & Ju, Ping & Wu, Feng & Pan, Xueping & Wang, Zhaoyu, 2022. "A systematic review on power system resilience from the perspective of generation, network, and load," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    5. Katal, Ali & Mortezazadeh, Mohammad & Wang, Liangzhu (Leon) & Yu, Haiyi, 2022. "Urban building energy and microclimate modeling – From 3D city generation to dynamic simulations," Energy, Elsevier, vol. 251(C).

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