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Improving the Energy Performance and Economic Benefits of Aged Residential Buildings by Retrofitting in Hot–Humid Regions of China

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  • Xiaolin Yang

    (School of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China)

  • Zhuoxi Chen

    (School of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China)

  • Yukai Zou

    (School of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China)

  • Fengdeng Wan

    (School of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China)

Abstract

The existing building stock faces the challenge of low energy efficiency and requires renovation and upgrading to meet society′s goals of carbon reduction and sustainable development. This study presents an optimization framework utilizing genetic algorithms to develop robust retrofit plans that balance the need for improved energy efficiency, cost-effectiveness considerations for householders, and uncertainties regarding climate conditions. A case study of an aged residential building in a hot and humid region of China is used to demonstrate the proposed method. The optimization results show a potential energy demand reduction of 81.5%. However, due to the relatively long time required to realize economic benefits from high investments, short-term optimization tends to favor solutions with high energy demand and low primary costs. To effectively reduce carbon emissions, it is recommended to consider the long-term economic benefits of retrofits and prioritize solutions with high energy efficiency. However, it is important to acknowledge that the expensive nature of retrofit investments may pose barriers to residents. Society should provide adequate support and guidance to facilitate residential renovation efforts.

Suggested Citation

  • Xiaolin Yang & Zhuoxi Chen & Yukai Zou & Fengdeng Wan, 2023. "Improving the Energy Performance and Economic Benefits of Aged Residential Buildings by Retrofitting in Hot–Humid Regions of China," Energies, MDPI, vol. 16(13), pages 1-21, June.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:13:p:4981-:d:1180503
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    References listed on IDEAS

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    Cited by:

    1. Rafael Batres & Yasaman Dadras & Farzad Mostafazadeh & Miroslava Kavgic, 2023. "MEVO: A Metamodel-Based Evolutionary Optimizer for Building Energy Optimization," Energies, MDPI, vol. 16(20), pages 1-24, October.
    2. Dawei Xia & Weien Xie & Jialiang Guo & Yukai Zou & Zhuotong Wu & Yini Fan, 2023. "Building Thermal and Energy Performance of Subtropical Terraced Houses under Future Climate Uncertainty," Sustainability, MDPI, vol. 15(16), pages 1-22, August.

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