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

Author

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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    Cited by:

    1. Sun, Yue & Luo, Zhiwen & Li, Yu & Zhao, Tianyi, 2024. "Grey-box model-based demand side management for rooftop PV and air conditioning systems in public buildings using PSO algorithm," Energy, Elsevier, vol. 296(C).
    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).

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