Study on dual-objective optimization method of life cycle energy consumption and economy of office building based on HypE genetic algorithm

• Published in: Energy and buildings Vol. 256; p. 111749
• Main Authors: Luo, Zhixing, Lu, Yiqing, Cang, Yujie, Yang, Liu
• Format: Journal Article
• Language: English
• Published: Lausanne Elsevier B.V 01.02.2022; Elsevier BV
• Subjects: Algorithms; Architectural design; Cost reduction; Design; Design optimization; Design parameters; Economic impact; Economy; Energy conservation; Energy consumption; Genetic algorithms; HypE genetic algorithm; Life cycle; Life cycles; Multi-objective optimization; Multiple objective analysis; Office buildings; Optimization; Life cycle; Energy consumption; HypE genetic algorithm; Multi-objective optimization; Economy
• ISSN: 0378-7788; 1872-6178
• DOI: 10.1016/j.enbuild.2021.111749

•A dual-objective optimization method from the perspective of designer and user.•Life-cycle energy and economy optimization for building Design Period based on HypE.•Use Low-E insulating glass, rotate the building 18°counterclockwise are beneficial.•Life cycle energy consumption and economy of the case are reduced by more than 15%. Multi-objective optimization of building life cycle energy consumption and cost is very essential for guiding design quantitatively. However, previous studies paid more attention to the potential effect of building energy saving and cost reduction based on design parameters from the perspective of designers, but ignored the potential brought by the willingness of users during operation stage. Therefore, this paper proposes a dual-objective optimization method based on the HypE algorithm, which takes into account users' energy saving intentions in order to maximize the potential of building life cycle energy saving and cost reduction. The application premise of this method is to establish energy and cost calculation model of building life cycle. The method was applied to the design of a small office building in Xi'an city of China, and the scheme were optimized by adjusting 7 design parameters and 2 parameters (cooling and heating temperature) related to the energy saving willingness of the users. The results show that the proposed method can reduce the energy consumption by 15.1%-18.8% and the cost by 2.2%-10.1% during life cycle. The results will continue to be reduced by up to 6.5% and 12.02% if the potential of uers' willingness to save energy continues to be realized. It is proved that the proposed method contributes to the comprehensive evaluation of energy saving and economic effects of architectural design during its life cycle and provides effective theoretical guidance and practical tools for architectural design and optimization.