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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| Published in | Scientific reports Vol. 15; no. 1; pp. 6504 - 19 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
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London
Nature Publishing Group UK
22.02.2025
Nature Publishing Group Nature Portfolio |
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| Abstract | 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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| AbstractList | 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. 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.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. Abstract 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. 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. |
| ArticleNumber | 6504 |
| Author | Wang, Xiaomin Yang, Wenting Xu, Juan Lu, Ziliang Fang, Yanjie |
| Author_xml | – sequence: 1 givenname: Juan surname: Xu fullname: Xu, Juan email: xujuan0626@chd.edu.cn organization: School of Architecture, Chang’an University – sequence: 2 givenname: Yanjie surname: Fang fullname: Fang, Yanjie organization: China Construction Eighth Engineering Division Decoration Engineering Co., LTD – sequence: 3 givenname: Wenting surname: Yang fullname: Yang, Wenting organization: School of Architecture, Chang’an University – sequence: 4 givenname: Ziliang surname: Lu fullname: Lu, Ziliang organization: School of Architecture, Chang’an University – sequence: 5 givenname: Xiaomin surname: Wang fullname: Wang, Xiaomin organization: School of Architecture, Chang’an University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/39987320$$D View this record in MEDLINE/PubMed |
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| Keywords | Building shape Qinba mountainous area Multi-objective optimization Low-energy dwelling Genetic algorithm |
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| Snippet | Rural areas in China play a significant position in society, with traditional dwellings reflecting local culture and lifestyles. However, the energy... Abstract Rural areas in China play a significant position in society, with traditional dwellings reflecting local culture and lifestyles. However, the energy... |
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| SubjectTerms | 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 |
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| Title | Multi-objective optimal research on low-energy dwellings design based on genetic algorithm in Qinba mountain region, China |
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