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<p>Rural areas in China play a significant position in society, with traditional dwellings reflecting local culture and lifestyles. However, the energy consumption of these dwellings has not been thoroughly quantified, despite their importance in the low-carbon energy conservation efforts. This study explores the influence of key design elements—such as orientation, plan form, window-to-wall ratio, and roof slope—on the energy consumption of rural dwellings. Using the Wallacei-X multi-objective optimization algorithm, we analyze the energy consumption of various dwelling layouts. The findings suggest that a design with a N-W60°, a plan length of 10.8&#xa0;m, a width of 8.9&#xa0;m, a window-to-wall ratio (WWR-E) of 0.2, and a roof slope of 5° can reduce annual energy consumption by approximately 5.59%. Sensitivity analysis reveals that the window-to-wall ratio on the east side (WWR-E) has the greatest influence on energy efficiency, followed by other design factors. This research offers valuable insights into low-energy solutions for rural dwellings in the Qinba Mountain region.</p>

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Multi-objective optimal research on low-energy dwellings design based on genetic algorithm in Qinba mountain region, China

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月22日

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  • Juan Xu,
  • Yanjie Fang,
  • Wenting Yang,
  • Ziliang Lu,
  • Xiaomin Wang

摘要

Rural areas in China play a significant position in society, with traditional dwellings reflecting local culture and lifestyles. However, the energy consumption of these dwellings has not been thoroughly quantified, despite their importance in the low-carbon energy conservation efforts. This study explores the influence of key design elements—such as orientation, plan form, window-to-wall ratio, and roof slope—on the energy consumption of rural dwellings. Using the Wallacei-X multi-objective optimization algorithm, we analyze the energy consumption of various dwelling layouts. The findings suggest that a design with a N-W60°, a plan length of 10.8 m, a width of 8.9 m, a window-to-wall ratio (WWR-E) of 0.2, and a roof slope of 5° can reduce annual energy consumption by approximately 5.59%. Sensitivity analysis reveals that the window-to-wall ratio on the east side (WWR-E) has the greatest influence on energy efficiency, followed by other design factors. This research offers valuable insights into low-energy solutions for rural dwellings in the Qinba Mountain region.