Multi-objective optimization design for rural houses in western zones of China. (4th July 2022)

• Record Type: Journal Article
• Authors: Shao, Teng; Zheng, Wuxing; Li, Xinxin; Yang, Weili; Wang, Ruixuan
• Is Part Of: Architectural science review. Volume 65:Number 4(2022)
• Page Start: 260
• Page End: 277
• Publication Date: 2022-07-04
• Subjects: Severe cold and cold regions -- rural house -- multi-objective optimization -- passive design variable -- building performance -- optimum combination; Architecture -- Periodicals; Building -- Periodicals; Engineering -- Periodicals; 720.5
• DOI: 10.1080/00038628.2022.2040412
• Languages: English
• ISSNs: 0003-8628

Abstract

Abstract : Limited by the climate, economic level and energy-saving awareness of rural residents in the western China, rural houses are still in a stage of high energy consumption (EC) and low comfort. The passive design strategies should be given priority to provide an optimal design mode. The challenge is to find the best combination of design parameters. In this paper, rural single-storey detached houses are taken as the research objects. Three conflicted indicators are set as the objective function, namely building EC, thermal comfort and economy. The investigated design variables include building orientation, insulating layer thickness, window width & type, and indoor design temperature. A methodology of combining EnergyPlus and MOBO is used for multi-objective optimization, thus getting the Pareto solutions and using the weighted sum method to obtain the optimum parameter combinations. The proposed methodology for simulation-based multi-objective optimization is a useful tool to facilitate decision-making in building design. Highlights An automated optimization method of combining EnergyPlus simulation software and MOBO optimization engine is proposed. The multi-objective method optimizes the building orientation, envelope and winter indoor temperature. Pareto non-dominated solutions for three conflict objective functions are obtained. The final optimum combination is determined by a weighted sum method.