Multi-Objective Optimization Design for Cold-Region Office Buildings Balancing Outdoor Thermal Comfort and Building Energy Consumption

Fei Guo, Shiyu Miao, Sheng Xu, Mingxuan Luo, Jing Dong () and Hongchi Zhang ()
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Fei Guo: School of Architecture and Fine Art, Dalian University of Technology, Dalian 116024, China
Shiyu Miao: School of Architecture and Fine Art, Dalian University of Technology, Dalian 116024, China
Sheng Xu: School of Architecture and Fine Art, Dalian University of Technology, Dalian 116024, China
Mingxuan Luo: School of Architecture and Fine Art, Dalian University of Technology, Dalian 116024, China
Jing Dong: School of Architecture and Fine Art, Dalian University of Technology, Dalian 116024, China
Hongchi Zhang: School of Architecture and Fine Art, Dalian University of Technology, Dalian 116024, China

Energies, 2024, vol. 18, issue 1, 1-21

Abstract: Performance parameters and generative design applications have redefined the human–machine collaborative relationship, challenging traditional architectural design paradigms and guiding the architectural design process toward a performance-based design transformation. This study proposes a multi-objective optimization (MOO) design approach based on performance simulation, utilizing the Grasshopper-EvoMass multi-objective optimization platform. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is applied to coordinate two performance metrics—outdoor thermal comfort and building energy loads—for the multi-objective optimization of architectural design. The results indicate that (1) a performance-based multi-objective optimization design workflow is established. Compared to the baseline design, the optimized building form shows a significant improvement in performance. The Pareto optimal solutions, under 2022 meteorological conditions, demonstrate an annual energy efficiency improvement of 16.55%, and the outdoor thermal neutrality ratio increases by 1.11%. These results suggest that the optimization approach effectively balances building energy loads and outdoor thermal comfort. (2) A total of 1500 building form solutions were generated, from which 16 optimal solutions were selected through the Pareto front method. The resulting Pareto optimal building layouts provide multiple feasible form configurations for the early-stage design phase.

Keywords: multi-objective optimization; building energy consumption; outdoor thermal comfort; office buildings (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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