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Performance-Oriented Parametric Optimization Design for Energy Efficiency of Rural Residential Buildings: A Case Study from China’s Hot Summer and Cold Winter Zone

Author

Listed:
  • Meiyan Wang

    (College of Landscape Architecture, Zhejiang A & F University, Hangzhou 311300, China)

  • Ying Xu

    (College of Landscape Architecture, Zhejiang A & F University, Hangzhou 311300, China)

  • Runtian Shen

    (College of Landscape Architecture, Zhejiang A & F University, Hangzhou 311300, China)

  • Yun Wu

    (College of Landscape Architecture, Zhejiang A & F University, Hangzhou 311300, China)

Abstract

With the implementation of the rural revitalization strategy, rural residences have become an essential component of China’s building energy conservation efforts. However, most existing research has focused more on urban buildings, with less attention given to rural residences. This study, taking rural residential buildings (RRBs) in the hot summer and cold winter zones in China as an example, proposes a more precise, two-stage optimization design framework using Rhino-Grasshopper for the overall optimization of RRBs. First, field surveys and numerical analysis of collected rural residential design drawings were conducted to clarify spatial characteristics and air conditioning usage. The parametric optimization design of RRBs was then conducted in two steps. The first step involves room function positioning, where spatial geometric models are established. Annual dynamic simulation analyses of AC (air conditioning) and AL (artificial lighting) energy consumption are performed to obtain energy intensity distribution maps. Based on the principle that “space with higher energy consumption is set in the location with lower energy consumption intensity” and the habit of functional space distribution, room function positioning, and adjustments are made. In the second step, the SPEA-2 genetic algorithm was applied for multi-objective optimization of room width, depth, WWR (window-to-wall ratio), SHGC (solar heat gain coefficient), and VLT (visible light transmittance), all based on the logical relationships of the building structure. The final Pareto front solution sets were obtained by multi-objective optimization simulation (MOO). A typical three-bay RRB was selected for application in this study, and the optimized design led to a total energy savings rate of 11% in annual AC and AL energy consumption.

Suggested Citation

  • Meiyan Wang & Ying Xu & Runtian Shen & Yun Wu, 2024. "Performance-Oriented Parametric Optimization Design for Energy Efficiency of Rural Residential Buildings: A Case Study from China’s Hot Summer and Cold Winter Zone," Sustainability, MDPI, vol. 16(19), pages 1-30, September.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:19:p:8330-:d:1485268
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    References listed on IDEAS

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    1. Xie Xie & Yang Ni & Tianzi Zhang, 2025. "Machine-Learning-Enhanced Building Performance-Guided Form Optimization of High-Rise Office Buildings in China’s Hot Summer and Warm Winter Zone—A Case Study of Guangzhou," Sustainability, MDPI, vol. 17(9), pages 1-27, May.
    2. Ahmad Walid Ayoobi & Mehmet Inceoğlu, 2024. "Developing an Optimized Energy-Efficient Sustainable Building Design Model in an Arid and Semi-Arid Region: A Genetic Algorithm Approach," Energies, MDPI, vol. 17(23), pages 1-31, December.

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