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

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.