A novel differential evolution method with a hierarchical decoder for the photovoltaic layout optimization problem
As photovoltaic technology advances, the scale of systems expands. A typical photovoltaic power plant spans over 1 km2 and includes more than 100,000 modules and 300 km of cabling, leading to substantial design complexities. Manual design processes can take weeks and often fail to guarantee cost-opt...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | International Journal of Electrical Power & Energy Systems |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0142061524006203 |
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| author | Yuanqing Yao Yibo Wang Hongjie Jia Yunfei Mu |
| author_facet | Yuanqing Yao Yibo Wang Hongjie Jia Yunfei Mu |
| author_sort | Yuanqing Yao |
| collection | DOAJ |
| description | As photovoltaic technology advances, the scale of systems expands. A typical photovoltaic power plant spans over 1 km2 and includes more than 100,000 modules and 300 km of cabling, leading to substantial design complexities. Manual design processes can take weeks and often fail to guarantee cost-optimal solutions. Consequently, an efficient and optimal layout design method for photovoltaic plants is crucial, as it enhances design efficiency while optimizing overall costs. This design method involves the precise placement of equipment and strategic configuration of cable connections. Challenges in this process arise from the need to accommodate various site shapes, equipment sizes, topological connections, and design constraints specific to power stations. To address these challenges, we develop a differential-evolution-based photovoltaic layout optimization method. Firstly, we propose a hierarchical decoder which includes a grided layout process coupled with a clustering method to zone the site and position equipment, followed by the application of the A* algorithm to determine the efficient cable paths. This process is further refined using the differential evolution algorithm, tailored to meet the constraints of photovoltaic plant design while enhancing the solution search scope. Results from benchmark cases demonstrate that the proposed method is effective across small, medium, and large cases, outperforming the most advanced methods in 38 out of 45 cases. The effectiveness of the zoning, pathfinding, and differential evolution mechanisms within the method has been verified through ablation studies. Moreover, in real power plant cases, this method has reduced overall costs by 44% compared to those of manual designs. |
| format | Article |
| id | doaj-art-65bc01782865445aa9f458ad5dc3bab6 |
| institution | Kabale University |
| issn | 0142-0615 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Electrical Power & Energy Systems |
| spelling | doaj-art-65bc01782865445aa9f458ad5dc3bab62025-01-19T06:23:54ZengElsevierInternational Journal of Electrical Power & Energy Systems0142-06152025-03-01164110397A novel differential evolution method with a hierarchical decoder for the photovoltaic layout optimization problemYuanqing Yao0Yibo Wang1Hongjie Jia2Yunfei Mu3Tianjin University, Tianjin, 300072, China; Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing, 100190, ChinaInstitute of Electrical Engineering, Chinese Academy of Sciences, Beijing, 100190, China; Corresponding author.Tianjin University, Tianjin, 300072, ChinaTianjin University, Tianjin, 300072, ChinaAs photovoltaic technology advances, the scale of systems expands. A typical photovoltaic power plant spans over 1 km2 and includes more than 100,000 modules and 300 km of cabling, leading to substantial design complexities. Manual design processes can take weeks and often fail to guarantee cost-optimal solutions. Consequently, an efficient and optimal layout design method for photovoltaic plants is crucial, as it enhances design efficiency while optimizing overall costs. This design method involves the precise placement of equipment and strategic configuration of cable connections. Challenges in this process arise from the need to accommodate various site shapes, equipment sizes, topological connections, and design constraints specific to power stations. To address these challenges, we develop a differential-evolution-based photovoltaic layout optimization method. Firstly, we propose a hierarchical decoder which includes a grided layout process coupled with a clustering method to zone the site and position equipment, followed by the application of the A* algorithm to determine the efficient cable paths. This process is further refined using the differential evolution algorithm, tailored to meet the constraints of photovoltaic plant design while enhancing the solution search scope. Results from benchmark cases demonstrate that the proposed method is effective across small, medium, and large cases, outperforming the most advanced methods in 38 out of 45 cases. The effectiveness of the zoning, pathfinding, and differential evolution mechanisms within the method has been verified through ablation studies. Moreover, in real power plant cases, this method has reduced overall costs by 44% compared to those of manual designs.http://www.sciencedirect.com/science/article/pii/S0142061524006203Photovoltaic plant designHierarchical decoderEquipment layoutCable routingDifferential evolution |
| spellingShingle | Yuanqing Yao Yibo Wang Hongjie Jia Yunfei Mu A novel differential evolution method with a hierarchical decoder for the photovoltaic layout optimization problem International Journal of Electrical Power & Energy Systems Photovoltaic plant design Hierarchical decoder Equipment layout Cable routing Differential evolution |
| title | A novel differential evolution method with a hierarchical decoder for the photovoltaic layout optimization problem |
| title_full | A novel differential evolution method with a hierarchical decoder for the photovoltaic layout optimization problem |
| title_fullStr | A novel differential evolution method with a hierarchical decoder for the photovoltaic layout optimization problem |
| title_full_unstemmed | A novel differential evolution method with a hierarchical decoder for the photovoltaic layout optimization problem |
| title_short | A novel differential evolution method with a hierarchical decoder for the photovoltaic layout optimization problem |
| title_sort | novel differential evolution method with a hierarchical decoder for the photovoltaic layout optimization problem |
| topic | Photovoltaic plant design Hierarchical decoder Equipment layout Cable routing Differential evolution |
| url | http://www.sciencedirect.com/science/article/pii/S0142061524006203 |
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