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A new method of generating extreme building energy year and its application

Author

Listed:
  • Li, Honglian
  • Zhang, Tiantian
  • Wang, An
  • Wang, Mengli
  • Huang, Jin
  • Hu, Yao

Abstract

In the early stage of building design, typical meteorological year (TMY) used for building energy consumption simulation which mainly representing average conditions, cannot reflect the building energy consumption under extreme weather conditions. Intensified climate change leads to global warming and frequent extreme events, therefore, generating meteorological years for simulating building energy consumption under extreme weather conditions is desperately needed. In this paper, a new method for generating extreme weather years—An extreme building energy year (EBEY) is proposed, which not only considers the influence of various meteorological parameters on building energy consumption, but also calculates the extreme intensity and occurrence time of multiple parameters using dynamic thresholds. The results show that the accuracy of using EBEY to simulate building energy consumption under extreme weather conditions is better than that of temperature-only extreme years, radiation-only extreme years, extreme meteorological years (EMY), typical cold years (TCY) and typical hot years (THY). In addition, this study verifies that combining TMY and EBEY data reduces the number of simulations without losing the accuracy of the simulation results.

Suggested Citation

  • Li, Honglian & Zhang, Tiantian & Wang, An & Wang, Mengli & Huang, Jin & Hu, Yao, 2023. "A new method of generating extreme building energy year and its application," Energy, Elsevier, vol. 278(PB).
    • Handle: RePEc:eee:energy:v:278:y:2023:i:pb:s0360544223014147
    DOI: 10.1016/j.energy.2023.128020
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    References listed on IDEAS

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    1. Li, Honglian & Yang, Yi & Lv, Kailin & Liu, Jing & Yang, Liu, 2020. "Compare several methods of select typical meteorological year for building energy simulation in China," Energy, Elsevier, vol. 209(C).
    2. Yang, Liu & Yan, Haiyan & Lam, Joseph C., 2014. "Thermal comfort and building energy consumption implications – A review," Applied Energy, Elsevier, vol. 115(C), pages 164-173.
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    Cited by:

    1. Li, Honglian & He, Xi & Hu, Yao & Lv, Wen & Yang, Liu, 2024. "Research on the generation method of missing hourly solar radiation data based on multiple neural network algorithm," Energy, Elsevier, vol. 287(C).

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