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 e...

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Bibliographic Details
Published inScientific reports Vol. 15; no. 1; pp. 6504 - 19
Main Authors Xu, Juan, Fang, Yanjie, Yang, Wenting, Lu, Ziliang, Wang, Xiaomin
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 22.02.2025
Nature Publishing Group
Nature Portfolio
Subjects
639/166
639/4077
Algorithms
Building shape
Clean energy
Energy conservation
Energy consumption
Energy efficiency
Genetic algorithm
Humanities and Social Sciences
Local culture
Low-energy dwelling
Mountain regions
Multi-objective optimization
multidisciplinary
Qinba mountainous area
Rural areas
Science
Science (multidisciplinary)
Sensitivity analysis
China
Building shape
Qinba mountainous area
Multi-objective optimization
Low-energy dwelling
Genetic algorithm
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Summary: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.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-025-90133-w