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| The Improved Partical Swarm Optimization Algorthim for Multiobjective Optimal Power Flow |
| Zhang Qin1, Zhang Jianmei2, Ma Qiang1, Wang Xianhong1 |
1. Nanchong Power Supply Company of Sichuan Electric Power Corporation, Nanchong, Sichuan 637000;
2. Skill Training Center of Sichuan Electric Power Corporation, Chengdu 610071 |
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Abstract The multiobjective optimimal power flow algorithm is researched in this paper. Using the improved partical swarm optimization algorthim to calculate power flow considering the cost and network loss. The fuzzy set theory is used in multiobjective function processing to make it a single objective. And the partical swarm optimization algorthim is improved through adjusting and particle position variable to avoid being into a local optimal. Using C means clustering algorithm for set esterase processing, and making the solution more satisfying the requirements of the homogenization. The correctness of the algorithm researched in this paper is proved through the IEEE system test.
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Published: 24 October 2017
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| Cite this article: |
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Zhang Qin,Zhang Jianmei,Ma Qiang等. The Improved Partical Swarm Optimization Algorthim for Multiobjective Optimal Power Flow[J]. Electrical Engineering, 2017, 18(10): 57-60.
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| URL: |
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http://dqjs.cesmedia.cn/EN/Y2017/V18/I10/57
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2017, Vol. 18 
