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A new method to develop typical weather years in different climates for building energy use studies

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  • Yang, Liu
  • Wan, Kevin K.W.
  • Li, Danny H.W.
  • Lam, Joseph C.

Abstract

Principal component analysis of 30-year long-term meteorological variables was conducted. Typical principal component years (TPCYs) were determined for Harbin, Beijing, Shanghai, Kunming and Hong Kong representing the five major architectural climates across China: severe cold, cold, hot summer and cold winter, mild, and hot summer and warm winter. In each climate zone, the TPCY was compared with the 30 individual years and the widely used typical meteorological year (TMY). The monthly principal component and the predicted total building energy consumption based on the TPCY and TMY were very close to the 30-year long-term mean estimation. TPCY for the 21st century in each of the five cities was also identified using predictions from general climate models. The TPCY approach is a good alternative to the TMY method. Firstly, predicted building energy use from TPCY is closer to the long-term estimation than that from the TMY in different climates. Secondly, because only monthly data are considered, the development of TPCY is much simpler and less time-consuming. This would have important applications in the regular updating of typical weather years for building energy studies and in the assessment of the impact of climate change on energy use in the built environment.

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  • Yang, Liu & Wan, Kevin K.W. & Li, Danny H.W. & Lam, Joseph C., 2011. "A new method to develop typical weather years in different climates for building energy use studies," Energy, Elsevier, vol. 36(10), pages 6121-6129.
    • Handle: RePEc:eee:energy:v:36:y:2011:i:10:p:6121-6129
    DOI: 10.1016/j.energy.2011.07.053
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    9. Li, Danny H.W. & Yang, Liu & Lam, Joseph C., 2012. "Impact of climate change on energy use in the built environment in different climate zones – A review," Energy, Elsevier, vol. 42(1), pages 103-112.
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    13. Haixiang Zang & Miaomiao Wang & Jing Huang & Zhinong Wei & Guoqiang Sun, 2016. "A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of China," Energies, MDPI, vol. 9(12), pages 1-19, December.
    14. Xinying Fan & Bin Chen & Changfeng Fu & Lingyun Li, 2020. "Research on the Influence of Abrupt Climate Changes on the Analysis of Typical Meteorological Year in China," Energies, MDPI, vol. 13(24), pages 1-16, December.
    15. Liu, Yan & Yang, Liu & Hou, Liqiang & Li, Shiyang & Yang, Jian & Wang, Qiuwang, 2017. "A porous building approach for modelling flow and heat transfer around and inside an isolated building on night ventilation and thermal mass," Energy, Elsevier, vol. 141(C), pages 1914-1927.
    16. Sun, Jingting & Li, Zhengrong & Xiao, Fu & Xiao, Jianzhuang, 2020. "Generation of typical meteorological year for integrated climate based daylight modeling and building energy simulation," Renewable Energy, Elsevier, vol. 160(C), pages 721-729.
    17. Zang, Haixiang & Cheng, Lilin & Ding, Tao & Cheung, Kwok W. & Wang, Miaomiao & Wei, Zhinong & Sun, Guoqiang, 2019. "Estimation and validation of daily global solar radiation by day of the year-based models for different climates in China," Renewable Energy, Elsevier, vol. 135(C), pages 984-1003.
    18. Li, Danny H.W. & Yang, Liu & Lam, Joseph C., 2013. "Zero energy buildings and sustainable development implications – A review," Energy, Elsevier, vol. 54(C), pages 1-10.
    19. Fan, Xinying, 2022. "A method for the generation of typical meteorological year data using ensemble empirical mode decomposition for different climates of China and performance comparison analysis," Energy, Elsevier, vol. 240(C).
    20. Chung, Mo & Park, Hwa-Choon, 2015. "Comparison of building energy demand for hotels, hospitals, and offices in Korea," Energy, Elsevier, vol. 92(P3), pages 383-393.
    21. Capeluto, I. Guedi & Ochoa, Carlos E., 2014. "Simulation-based method to determine climatic energy strategies of an adaptable building retrofit façade system," Energy, Elsevier, vol. 76(C), pages 375-384.
    22. Li, Honglian & Huang, Jin & Hu, Yao & Wang, Shangyu & Liu, Jing & Yang, Liu, 2021. "A new TMY generation method based on the entropy-based TOPSIS theory for different climatic zones in China," Energy, Elsevier, vol. 231(C).
    23. Verbai, Zoltán & Kocsis, Imre & Kalmár, Ferenc, 2015. "Outdoor dry bulb heating design temperatures for Hungary," Energy, Elsevier, vol. 93(P2), pages 1404-1412.
    24. Nik, Vahid M., 2016. "Making energy simulation easier for future climate – Synthesizing typical and extreme weather data sets out of regional climate models (RCMs)," Applied Energy, Elsevier, vol. 177(C), pages 204-226.

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