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Urban microclimate and building energy models: A review of the latest progress in coupling strategies

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Listed:
  • Sezer, Nurettin
  • Yoonus, Hamad
  • Zhan, Dongxue
  • Wang, Liangzhu (Leon)
  • Hassan, Ibrahim Galal
  • Rahman, Mohammad Azizur

Abstract

Climatic conditions are different in cities than in their geographical environment. Precise representation of the climatic parameters within an urban context is crucial for obtaining realistic results from building energy simulation studies. To this end, many research groups aim to include the best representative urban microclimate parameters as input to building energy simulations. Recently, coupling strategies have been adopted to facilitate a rapid and accurate exchange of information between urban microclimate and building energy models to output more realistic building energy simulation results that cannot be obtained in solo simulations. Despite the presence of many review articles on urban microclimate modeling and building energy simulation, a review of coupling strategies between these two has not been studied in recent literature. In this context, the present article goes beyond available studies with an up-to-date review of the coupling strategies between urban microclimate and building energy models. Available tools for urban microclimate simulation and building energy simulation are presented. The coupling strategies between these two different simulation tools are elucidated. Opportunities and limitations of coupling strategies are provided. Further, the achievements of recent research on adopting these coupling strategies are summarized, compiled, and discussed. Briefly, this article presents the urban microclimate and building energy simulation tools widely used in the literature with a particular emphasis on the research progress of coupling strategies between the two tools.

Suggested Citation

  • Sezer, Nurettin & Yoonus, Hamad & Zhan, Dongxue & Wang, Liangzhu (Leon) & Hassan, Ibrahim Galal & Rahman, Mohammad Azizur, 2023. "Urban microclimate and building energy models: A review of the latest progress in coupling strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
  • Handle: RePEc:eee:rensus:v:184:y:2023:i:c:s1364032123004343
    DOI: 10.1016/j.rser.2023.113577
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    References listed on IDEAS

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    1. Li, Xiaoma & Zhou, Yuyu & Yu, Sha & Jia, Gensuo & Li, Huidong & Li, Wenliang, 2019. "Urban heat island impacts on building energy consumption: A review of approaches and findings," Energy, Elsevier, vol. 174(C), pages 407-419.
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    2. Gao, Yuan & Hu, Zehuan & Shi, Shanrui & Chen, Wei-An & Liu, Mingzhe, 2024. "Adversarial discriminative domain adaptation for solar radiation prediction: A cross-regional study for zero-label transfer learning in Japan," Applied Energy, Elsevier, vol. 359(C).
    3. Or Yatzkan & Reuven Cohen & Eyal Yaniv & Orit Rotem-Mindali, 2025. "Urban Energy Transitions: A Systematic Review," Land, MDPI, vol. 14(3), pages 1-24, March.
    4. Bian, Chenhang & Cheung, Ka Lung & Chen, Xi & Lee, Chi Chung, 2025. "Integrating microclimate modelling with building energy simulation and solar photovoltaic potential estimation: The parametric analysis and optimization of urban design," Applied Energy, Elsevier, vol. 380(C).
    5. Gao, Yuan & Hu, Zehuan & Chen, Wei-An & Liu, Mingzhe, 2024. "Solutions to the insufficiency of label data in renewable energy forecasting: A comparative and integrative analysis of domain adaptation and fine-tuning," Energy, Elsevier, vol. 302(C).

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