Multi-phase framework for optimization of thermal and daylight performance of residential buildings based on the combination of ventilation and window design

• Published in: Journal of Asian architecture and building engineering Vol. 20; no. 6; pp. 785 - 805
• Main Authors: Wang, Jiahe, Mae, Masayuki, Taniguchi, Keiichiro, Cheng, Yanmeng, Yagi, Shigekazu, Saito, Koichiro
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 02.11.2021; Taylor & Francis Group
• Subjects: energy efficiency; multi-objective optimization; natural ventilation; Residential building; thermal comfort
• DOI: 10.1080/13467581.2020.1814304
• ISSN: 1346-7581

The environmental design of residential buildings is an arduous process involving a large number of parameters and objectives . Additionally, with the development trend of high-performance housing around the world, its disadvantage - the risk of overheating - has begun to increase, which further shows the importance of comprehensive optimization of residential buildings. This study presents a highly targeted optimization framework for residential buildings based on the adjustment of window-related parameters coupled with various natural ventilation patterns. Multiple phases are carried out in this optimization framework to optimizes three objectives, i.e. energy consumption, thermal comfort, daylight environment simultaneously. Phase 1 applies various natural ventilation patterns to explore the improvement potential of ventilation patterns. Phase 2 implements a genetic algorithm to achieve the Pareto optimization of window-related parameters. Phase 3 filters more robust Pareto-optimal based on Multi-Criteria Decision-Making logic to meet the different needs of different skateboards and architectures. The innovation and scientific significance lie in parameters include both the building envelope elements and ventilation patterns, as well as highly targeted for residential building. The results show that natural ventilation effectively improves the potential for simultaneous optimization of multiple objectives, and the optimization framework can adapt to residential buildings with various envelope insulation performance.