An Improved Symbiosis Particle Swarm Optimization for Solving Economic Load Dispatch Problem
To realize the sustainable development of social economy, energy conservation and emission reduction has become one of the problems that must be considered in the current power system. Under the electric power market system, the economic load dispatch problem not only is important but also has pract...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2021/8869477 |
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| author | Jianxia Zhang Jianxin Zhang Feng Zhang Minglu Chi Linbin Wan |
| author_facet | Jianxia Zhang Jianxin Zhang Feng Zhang Minglu Chi Linbin Wan |
| author_sort | Jianxia Zhang |
| collection | DOAJ |
| description | To realize the sustainable development of social economy, energy conservation and emission reduction has become one of the problems that must be considered in the current power system. Under the electric power market system, the economic load dispatch problem not only is important but also has practical significance and broad application prospects. In order to minimize the costs of electric-power generation, the load capacity should be reasonably assigned among many different generating sets. In this paper, an improved symbiosis particle swarm optimization algorithm was proposed, aiming at providing a better solution to this problem. First of all, a mathematical model was established with certain constraints, which successfully converted the practical problem into a mathematical one. Then, to balance the global optimization and local search capability, an improved symbiosis particle swarm optimization algorithm with mutualistic symbiosis strategy in nature was presented. The improved symbiosis particle swarm optimization algorithm consisted of three swarms inspired by the proverb “two heads are better than one,” and its specific analysis was through the standard test functions. At last, the economic load dispatch problem could be optimized by the proposed improved symbiosis particle swarm optimization algorithm. In addition, two different kinds of practical examples were also adopted for algorithm evaluation. From the simulation results, it can be seen clearly that the costs of electric-power generation gained were the lowest compared with the results of particle swarm optimization algorithm, improved chaos particle swarm optimization algorithm, and symbiotic organisms search algorithm, well demonstrating the effectiveness of the improved symbiosis particle swarm optimization algorithm in solving the economic load dispatch problem. |
| format | Article |
| id | doaj-art-d41028f569094d50a3dbe98ddd9dabce |
| institution | DOAJ |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-d41028f569094d50a3dbe98ddd9dabce2025-08-20T03:23:47ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552021-01-01202110.1155/2021/88694778869477An Improved Symbiosis Particle Swarm Optimization for Solving Economic Load Dispatch ProblemJianxia Zhang0Jianxin Zhang1Feng Zhang2Minglu Chi3Linbin Wan4School of Intelligent Engineering, Henan Institute of Technology, Xinxiang 453003, ChinaSchool of Computer Science and Engineering, Dalian Minzu University, Dalian 116600, ChinaSchool of Intelligent Engineering, Henan Institute of Technology, Xinxiang 453003, ChinaSchool of Intelligent Engineering, Henan Institute of Technology, Xinxiang 453003, ChinaStudent Affairs Office, Henan Institute of Technology, Xinxiang 453003, ChinaTo realize the sustainable development of social economy, energy conservation and emission reduction has become one of the problems that must be considered in the current power system. Under the electric power market system, the economic load dispatch problem not only is important but also has practical significance and broad application prospects. In order to minimize the costs of electric-power generation, the load capacity should be reasonably assigned among many different generating sets. In this paper, an improved symbiosis particle swarm optimization algorithm was proposed, aiming at providing a better solution to this problem. First of all, a mathematical model was established with certain constraints, which successfully converted the practical problem into a mathematical one. Then, to balance the global optimization and local search capability, an improved symbiosis particle swarm optimization algorithm with mutualistic symbiosis strategy in nature was presented. The improved symbiosis particle swarm optimization algorithm consisted of three swarms inspired by the proverb “two heads are better than one,” and its specific analysis was through the standard test functions. At last, the economic load dispatch problem could be optimized by the proposed improved symbiosis particle swarm optimization algorithm. In addition, two different kinds of practical examples were also adopted for algorithm evaluation. From the simulation results, it can be seen clearly that the costs of electric-power generation gained were the lowest compared with the results of particle swarm optimization algorithm, improved chaos particle swarm optimization algorithm, and symbiotic organisms search algorithm, well demonstrating the effectiveness of the improved symbiosis particle swarm optimization algorithm in solving the economic load dispatch problem.http://dx.doi.org/10.1155/2021/8869477 |
| spellingShingle | Jianxia Zhang Jianxin Zhang Feng Zhang Minglu Chi Linbin Wan An Improved Symbiosis Particle Swarm Optimization for Solving Economic Load Dispatch Problem Journal of Electrical and Computer Engineering |
| title | An Improved Symbiosis Particle Swarm Optimization for Solving Economic Load Dispatch Problem |
| title_full | An Improved Symbiosis Particle Swarm Optimization for Solving Economic Load Dispatch Problem |
| title_fullStr | An Improved Symbiosis Particle Swarm Optimization for Solving Economic Load Dispatch Problem |
| title_full_unstemmed | An Improved Symbiosis Particle Swarm Optimization for Solving Economic Load Dispatch Problem |
| title_short | An Improved Symbiosis Particle Swarm Optimization for Solving Economic Load Dispatch Problem |
| title_sort | improved symbiosis particle swarm optimization for solving economic load dispatch problem |
| url | http://dx.doi.org/10.1155/2021/8869477 |
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