Multi-objective optimization of building envelope of rural housing in the severely cold region of China based on energy consumption, thermal comfort and cost-effectiveness

被引:0
作者
Zhai, Xue [1 ,2 ,3 ,4 ]
He, Zijian [1 ,2 ]
Wang, Ran [1 ,2 ,3 ,4 ]
Lu, Shilei [1 ,2 ]
Zhang, Li [5 ]
机构
[1] Tianjin Univ, Sch Environm Sci & Engn, 92,Weijin Rd, Tianjin 300072, Peoples R China
[2] Tianjin Univ, Tianjin Key Lab Built Environm & Energy Applicat, Tianjin, Peoples R China
[3] State Key Lab Bldg Safety & Built Environm, Beijing, Peoples R China
[4] Natl Engn Res Ctr Bldg Technol, Beijing, Peoples R China
[5] China Aerosp Construct Engn Grp Co Ltd, Beijing, Peoples R China
关键词
Rural building; Indoor thermal comfort; Scenario analyses; Chebyshev inequality; Multi-objective optimization; DESIGN; PERFORMANCE; EFFICIENCY; ENVIRONMENT; INSULATION; CHALLENGES; WINDOW; FACADE;
D O I
10.1177/1420326X241308559
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The performance of rural residential buildings has a great energy-saving potential due to the great spontaneity and ignorance of the rural residential construction. To solve this problem, this paper provides a multi-objective optimization model based on Chebyshev inequality. The model takes energy consumption, indoor thermal comfort, project cost as optimization objectives and considers operating conditions in winter and summer. This study taking a rural residential house as an example and analysed the influence of its envelope parameters on building performance using EnergyPlus. The parameters of the building envelope were optimized, which verified the superiority of the method. Optimization results showed that the heating energy consumption was reduced by 29%, and the air conditioning energy consumption was reduced by 6%. This study analysed the relationship between the building energy consumption, indoor thermal comfort and the cost by multi-objective optimization method, to provide a new research idea for rural residential research. Optimal design solutions were generated under various weighting coefficients. The model aimed to meet the climatic and economic conditions of northern China and similar regions. Therefore, based on these optimization results, decision-makers can choose optimal design and construction solutions according to their own will.
引用
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页数:17
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