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Development of an Integrated Performance Design Platform for Residential Buildings Based on Climate Adaptability

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  • Zhixing Li

    (School of Design and Architecture, Zhejiang University of Technology, Hangzhou 310023, China)

  • Mimi Tian

    (School of Design and Architecture, Zhejiang University of Technology, Hangzhou 310023, China)

  • Yafei Zhao

    (Solearth Architecture Research Center, Building Information Technology Innovation Laboratory (BITI Lab), Hong Kong 999077, China)

  • Zhao Zhang

    (Faculty of Design, Architecture and Building, University of Technology Sydney, Sydney 2007, Australia)

  • Yuxi Ying

    (School of Design and Architecture, Zhejiang University of Technology, Hangzhou 310023, China)

Abstract

Building energy waste has become one of the major challenges confronting the world today, so specifications and targets for building energy efficiency have been put forward in countries around the world in recent years. The schematic design stage matters a lot for building energy efficiency, while most architects nowadays are less likely to make energy efficiency design decisions in this stage due to the lack of necessary means and methods for analysis. An integrated multi-objective multivariate framework for optimization analysis is proposed for the schematic design stage in the paper. Here, the design parameters of the building morphology and the design parameters of the building envelope are integrated for analysis, and an integrated performance prediction model is established for low-rise and medium-rise residential buildings. Then, a comparison of the performance indicators of low-rise and medium-rise residential buildings under five typical urban climatic conditions is carried out, and the change patterns of the lighting environment, thermal environment, building energy demand, and life cycle cost of residential buildings in each city under different morphological parameters and design parameters of the building envelope are summarized. Specific analysis methods and practical tools are provided in the study for architectural design to ensure thermal comfort, lighting comfort, low energy consumption, and low life-cycle cost requirement, and this design method can inspire and guide the climate adaptation analysis and design process of low-rise and medium-rise residential buildings in China, improve architects’ perception of energy-saving design principles of low-rise and medium-rise residential buildings on the ontological level, as well as provide them with a method to follow and a case to follow in the actual design process.

Suggested Citation

  • Zhixing Li & Mimi Tian & Yafei Zhao & Zhao Zhang & Yuxi Ying, 2021. "Development of an Integrated Performance Design Platform for Residential Buildings Based on Climate Adaptability," Energies, MDPI, vol. 14(24), pages 1-44, December.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:24:p:8223-:d:697001
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    References listed on IDEAS

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    1. Zhixing Li & Mimi Tian & Xiaoqing Zhu & Shujing Xie & Xin He, 2022. "A Review of Integrated Design Process for Building Climate Responsiveness," Energies, MDPI, vol. 15(19), pages 1-35, September.
    2. Yingtao Qi & Xiaodi Li & Yupeng Wang & Dian Zhou, 2023. "Research on Indoor Thermal Environment Analysis and Optimization Strategy of Rural Dwellings around Xi’an Based on PET Evaluation," Sustainability, MDPI, vol. 15(10), pages 1-25, May.
    3. Chen, Ruijun & Tsay, Yaw-Shyan & Zhang, Ting, 2023. "A multi-objective optimization strategy for building carbon emission from the whole life cycle perspective," Energy, Elsevier, vol. 262(PA).
    4. Kang, Yiting & Zhang, Dongjie & Cui, Yu & Xu, Wei & Lu, Shilei & Wu, Jianlin & Hu, Yiqun, 2024. "Integrated passive design method optimized for carbon emissions, economics, and thermal comfort of zero-carbon buildings," Energy, Elsevier, vol. 295(C).
    5. Carlos Henrique Valério de Moraes & Jonas Lopes de Vilas Boas & Germano Lambert-Torres & Gilberto Capistrano Cunha de Andrade & Claudio Inácio de Almeida Costa, 2022. "Intelligent Power Distribution Restoration Based on a Multi-Objective Bacterial Foraging Optimization Algorithm," Energies, MDPI, vol. 15(4), pages 1-23, February.

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