Multi-Objective Optimization Design for Cold-Region Office Buildings Balancing Outdoor Thermal Comfort and Building Energy Consumption
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-obj...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/18/1/62 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841549294122827776 |
|---|---|
| author | Fei Guo Shiyu Miao Sheng Xu Mingxuan Luo Jing Dong Hongchi Zhang |
| author_facet | Fei Guo Shiyu Miao Sheng Xu Mingxuan Luo Jing Dong Hongchi Zhang |
| author_sort | Fei Guo |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-b1ee9120a1214cae953922d1b7deb40c |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-b1ee9120a1214cae953922d1b7deb40c2025-01-10T13:16:58ZengMDPI AGEnergies1996-10732024-12-011816210.3390/en18010062Multi-Objective Optimization Design for Cold-Region Office Buildings Balancing Outdoor Thermal Comfort and Building Energy ConsumptionFei Guo0Shiyu Miao1Sheng Xu2Mingxuan Luo3Jing Dong4Hongchi Zhang5School of Architecture and Fine Art, Dalian University of Technology, Dalian 116024, ChinaSchool of Architecture and Fine Art, Dalian University of Technology, Dalian 116024, ChinaSchool of Architecture and Fine Art, Dalian University of Technology, Dalian 116024, ChinaSchool of Architecture and Fine Art, Dalian University of Technology, Dalian 116024, ChinaSchool of Architecture and Fine Art, Dalian University of Technology, Dalian 116024, ChinaSchool of Architecture and Fine Art, Dalian University of Technology, Dalian 116024, ChinaPerformance 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.https://www.mdpi.com/1996-1073/18/1/62multi-objective optimizationbuilding energy consumptionoutdoor thermal comfortoffice buildings |
| spellingShingle | Fei Guo Shiyu Miao Sheng Xu Mingxuan Luo Jing Dong Hongchi Zhang Multi-Objective Optimization Design for Cold-Region Office Buildings Balancing Outdoor Thermal Comfort and Building Energy Consumption Energies multi-objective optimization building energy consumption outdoor thermal comfort office buildings |
| title | Multi-Objective Optimization Design for Cold-Region Office Buildings Balancing Outdoor Thermal Comfort and Building Energy Consumption |
| title_full | Multi-Objective Optimization Design for Cold-Region Office Buildings Balancing Outdoor Thermal Comfort and Building Energy Consumption |
| title_fullStr | Multi-Objective Optimization Design for Cold-Region Office Buildings Balancing Outdoor Thermal Comfort and Building Energy Consumption |
| title_full_unstemmed | Multi-Objective Optimization Design for Cold-Region Office Buildings Balancing Outdoor Thermal Comfort and Building Energy Consumption |
| title_short | Multi-Objective Optimization Design for Cold-Region Office Buildings Balancing Outdoor Thermal Comfort and Building Energy Consumption |
| title_sort | multi objective optimization design for cold region office buildings balancing outdoor thermal comfort and building energy consumption |
| topic | multi-objective optimization building energy consumption outdoor thermal comfort office buildings |
| url | https://www.mdpi.com/1996-1073/18/1/62 |
| work_keys_str_mv | AT feiguo multiobjectiveoptimizationdesignforcoldregionofficebuildingsbalancingoutdoorthermalcomfortandbuildingenergyconsumption AT shiyumiao multiobjectiveoptimizationdesignforcoldregionofficebuildingsbalancingoutdoorthermalcomfortandbuildingenergyconsumption AT shengxu multiobjectiveoptimizationdesignforcoldregionofficebuildingsbalancingoutdoorthermalcomfortandbuildingenergyconsumption AT mingxuanluo multiobjectiveoptimizationdesignforcoldregionofficebuildingsbalancingoutdoorthermalcomfortandbuildingenergyconsumption AT jingdong multiobjectiveoptimizationdesignforcoldregionofficebuildingsbalancingoutdoorthermalcomfortandbuildingenergyconsumption AT hongchizhang multiobjectiveoptimizationdesignforcoldregionofficebuildingsbalancingoutdoorthermalcomfortandbuildingenergyconsumption |