A multi-objective optimization design method for gymnasium facade shading ratio integrating energy load and daylight comfort

• DOI: 10.1016/j.buildenv.2021.108527
• Publication Date: 2021-10-30T14:58:34Z
• Authors: Zhaoxiang Fan; Mengxuan Liu; Shuoning Tang
• Keywords: 13. Climate action; 11. Sustainability; 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology; 7. Clean energy

Abstract The large-scale use of curtain walls in stadiums and other public buildings will cause glare and increase the burden of energy consumption, especially in summer. In the early stage of the design, the optimization of the shading devices directly affects the decision-making of the building facade. This research proposes a multi-objective facade optimization method (MOO) for stadium design, using image density atlas (IDA) to provide decision-making basis for facade shading ratio (FSR) optimization in the preliminary design process of gymnasium. In contrast to the traditional design method, the optimized design framework proposed in this study will achieve the balance optimization among contradictory goals of daylight comfort and solar radiation at the same time to optimize the daylighting performance while avoiding glare and reducing energy burden. In this study, a gymnasium in Xiong'an, Beijing was selected as the test case. Researchers took the hourly average illuminance, hourly average solar radiation accumulation, and glare index during the opening hours of the gymnasium in summer (August) as the optimization goals. Then, the genetic algorithm SPEA-2 was used to explore the Pareto frontier solution set of FSR. The optimization scheme FSR = 0.37 is formed through comparison and screening. The research results achieved a 38.5% reduction in DGP, a 54% reduction in solar radiation, and control of illuminance loss within the acceptable range. The case study reveals the importance of FSR optimization to the indoor daylight environment of gymnasium in summer, and how parameter changes affect the rules of various metrics.