An Improved Particle Swarm Optimization with Biogeography-Based Learning Strategy for Economic Dispatch Problems
Economic dispatch (ED) plays an important role in power system operation, since it can decrease the operating cost, save energy resources, and reduce environmental load. This paper presents an improved particle swarm optimization called biogeography-based learning particle swarm optimization (BLPSO)...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/7289674 |
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| author | Xu Chen Bin Xu Wenli Du |
| author_facet | Xu Chen Bin Xu Wenli Du |
| author_sort | Xu Chen |
| collection | DOAJ |
| description | Economic dispatch (ED) plays an important role in power system operation, since it can decrease the operating cost, save energy resources, and reduce environmental load. This paper presents an improved particle swarm optimization called biogeography-based learning particle swarm optimization (BLPSO) for solving the ED problems involving different equality and inequality constraints, such as power balance, prohibited operating zones, and ramp-rate limits. In the proposed BLPSO, a biogeography-based learning strategy is employed in which particles learn from each other based on the quality of their personal best positions, and thus it can provide a more efficient balance between exploration and exploitation. The proposed BLPSO is applied to solve five ED problems and compared with other optimization techniques in the literature. Experimental results demonstrate that the BLPSO is a promising approach for solving the ED problems. |
| format | Article |
| id | doaj-art-8e79255d4e4d40b0ac0910e1de2d9512 |
| institution | OA Journals |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-8e79255d4e4d40b0ac0910e1de2d95122025-08-20T02:09:21ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/72896747289674An Improved Particle Swarm Optimization with Biogeography-Based Learning Strategy for Economic Dispatch ProblemsXu Chen0Bin Xu1Wenli Du2School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, 212013 Jiangsu, ChinaSchool of Mechanical Engineering, Shanghai University of Engineering Science, Shanghai 201620, ChinaKey Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, ChinaEconomic dispatch (ED) plays an important role in power system operation, since it can decrease the operating cost, save energy resources, and reduce environmental load. This paper presents an improved particle swarm optimization called biogeography-based learning particle swarm optimization (BLPSO) for solving the ED problems involving different equality and inequality constraints, such as power balance, prohibited operating zones, and ramp-rate limits. In the proposed BLPSO, a biogeography-based learning strategy is employed in which particles learn from each other based on the quality of their personal best positions, and thus it can provide a more efficient balance between exploration and exploitation. The proposed BLPSO is applied to solve five ED problems and compared with other optimization techniques in the literature. Experimental results demonstrate that the BLPSO is a promising approach for solving the ED problems.http://dx.doi.org/10.1155/2018/7289674 |
| spellingShingle | Xu Chen Bin Xu Wenli Du An Improved Particle Swarm Optimization with Biogeography-Based Learning Strategy for Economic Dispatch Problems Complexity |
| title | An Improved Particle Swarm Optimization with Biogeography-Based Learning Strategy for Economic Dispatch Problems |
| title_full | An Improved Particle Swarm Optimization with Biogeography-Based Learning Strategy for Economic Dispatch Problems |
| title_fullStr | An Improved Particle Swarm Optimization with Biogeography-Based Learning Strategy for Economic Dispatch Problems |
| title_full_unstemmed | An Improved Particle Swarm Optimization with Biogeography-Based Learning Strategy for Economic Dispatch Problems |
| title_short | An Improved Particle Swarm Optimization with Biogeography-Based Learning Strategy for Economic Dispatch Problems |
| title_sort | improved particle swarm optimization with biogeography based learning strategy for economic dispatch problems |
| url | http://dx.doi.org/10.1155/2018/7289674 |
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