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A comprehensive sensitivity study of major passive design parameters for the public rental housing development in Hong Kong

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  • Chen, Xi
  • Yang, Hongxing
  • Zhang, Weilong

Abstract

This paper presents a comprehensive SA (sensitivity analysis) of the typical PRH (public rental housing) development in Hong Kong based on a combined building energy, daylight and AFN (airflow network) simulation. A generic building model is constructed with a proposed MM (mixed-mode) ventilation control strategy to fulfill the thermal comfort requirement in the local green building guidance. The numerical modeling results are used to conduct both local and global sensitivity analyses to determine the relative importance of major passive design parameters, which comprehensively cover design aspects of the building layout, envelop thermophysics, building geometry and infiltration & air-tightness. The calculated global and local sensitivity indices on the cooling energy prove that the window solar heat gain coefficient, window to ground ratio, external obstruction and overhang projection fraction are the four most influential passive design factors. Similar results are also obtained when the lighting energy is specified as the output of the sensitivity analysis. The optimized building model derived from the sensitivity analysis is anticipated to achieve an energy saving of 41.6% compared to the baseline model as stipulated by the local building regulation. It is believed that sensitivity analysis is useful for identifying crucial design parameters to facilitate further optimization of the building performance in early architectural design stages.

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  • Chen, Xi & Yang, Hongxing & Zhang, Weilong, 2015. "A comprehensive sensitivity study of major passive design parameters for the public rental housing development in Hong Kong," Energy, Elsevier, vol. 93(P2), pages 1804-1818.
    • Handle: RePEc:eee:energy:v:93:y:2015:i:p2:p:1804-1818
    DOI: 10.1016/j.energy.2015.10.061
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    References listed on IDEAS

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    Cited by:

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    2. Wadu Mesthrige Jayantha & Lebunu Hewage Udara Willhelm Abeydeera, 2019. "Housing Consumption of the “Soon-to-Retire” in Hong Kong: A Cross-Sectional Regression Analysis," Asian Journal of Economics and Empirical Research, Asian Online Journal Publishing Group, vol. 6(1), pages 76-84.
    3. Saurbayeva, Assemgul & Memon, Shazim Ali & Kim, Jong, 2023. "Integrated multi-stage sensitivity analysis and multi-objective optimization approach for PCM integrated residential buildings in different climate zones," Energy, Elsevier, vol. 278(PB).
    4. Chen, Xi & Yang, Hongxing, 2018. "Integrated energy performance optimization of a passively designed high-rise residential building in different climatic zones of China," Applied Energy, Elsevier, vol. 215(C), pages 145-158.
    5. Chen, Xi & Yang, Hongxing & Wang, Yuanhao, 2017. "Parametric study of passive design strategies for high-rise residential buildings in hot and humid climates: miscellaneous impact factors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 442-460.
    6. Yingling Shi & Xinping Liu, 2019. "Research on the Literature of Green Building Based on the Web of Science: A Scientometric Analysis in CiteSpace (2002–2018)," Sustainability, MDPI, vol. 11(13), pages 1-22, July.
    7. Chen, Xi & Yang, Hongxing, 2017. "A multi-stage optimization of passively designed high-rise residential buildings in multiple building operation scenarios," Applied Energy, Elsevier, vol. 206(C), pages 541-557.
    8. Naji, Sareh & Aye, Lu & Noguchi, Masa, 2021. "Sensitivity analysis on energy performance, thermal and visual discomfort of a prefabricated house in six climate zones in Australia," Applied Energy, Elsevier, vol. 298(C).
    9. Du, Jiyun & Yang, Hongxing & Shen, Zhicheng & Chen, Jian, 2017. "Micro hydro power generation from water supply system in high rise buildings using pump as turbines," Energy, Elsevier, vol. 137(C), pages 431-440.
    10. Zhang, Weilong & Lu, Lin & Peng, Jinqing, 2017. "Evaluation of potential benefits of solar photovoltaic shadings in Hong Kong," Energy, Elsevier, vol. 137(C), pages 1152-1158.
    11. Chen, Xi & Yang, Hongxing & Sun, Ke, 2017. "Developing a meta-model for sensitivity analyses and prediction of building performance for passively designed high-rise residential buildings," Applied Energy, Elsevier, vol. 194(C), pages 422-439.

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