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The Research for Dynamic Distribution Network Reconfiguration based on Hybrid Optimization Algorithm |
Shi Huizhe1, Liu Zhipeng2, Zhong Wenqiang3 |
1. Shandong University of Science and Technology, Qingdao, Shandong 266590; 2. Hainan State Grid Corporation Dispatch and Control Center, Haikou 570203; 3. State Grid Pingdu Power Supply Company, Pingdu, Shandong 266000 |
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Abstract The proposed approach presents a hybrid algorithm which combines the Chaotic Particle Swarm Optimization and Teaching-Learning Optimization to overcome the Distribution Network Reconfiguration problem. Establish the mathematical model that bases on the minimum cost of operating, the minimum of network loss and the least number of switching operations. Form the comprehensive index including network loss and voltage deviation by the normalized processing.Set the maximum standard deviation of it and the maximum number of system reconstruction, determine the reconstruction period. This approach combines the Chaotic Particle Swarm Optimization and Teaching-Learning Optimization to find the global optima in more efficient way.In order to tune the inertia weight factor dynamically in distribution network reconfiguration, a chaotic framework is introduced to the PSO algorithm. Meanwhile the hybrid algorithm which include Teaching-Learning Optimization can guarantee diversity, limit the initial population premature convergence and improve the ability of the algorithm optimization. Finally, to validate the effectiveness and reasonableness of the proposed algorithm it is applied to IEEE 33 systems.
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Published: 22 June 2016
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Cite this article: |
Shi Huizhe,Liu Zhipeng,Zhong Wenqiang. The Research for Dynamic Distribution Network Reconfiguration based on Hybrid Optimization Algorithm[J]. Electrical Engineering, 2016, 17(6): 41-46.
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URL: |
http://dqjs.cesmedia.cn/EN/Y2016/V17/I6/41
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