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文章摘要
基于环路矩阵分块重组策略的配电网重构
Reconfiguration of Distribution Network Based on Loop Matrix Block-Recombination Strategy
Received:November 12, 2018  Revised:November 13, 2018
DOI:10.19753/j.issn1001-1390.2020.06.006
中文关键词: 配电网重构  不可行解  解空间分解  环路矩阵
英文关键词: Reconfiguration of distribution network, infeasible solution, decomposition of solution space, loop matrix
基金项目:
Author NameAffiliationE-mail
Chen Xin* School of Electrical Engineering and Information of Sichuan University 245867074@qq.com 
Zhou Buxiang School of Electrical Engineering and Information of Sichuan University 2642479475@qq.com 
Yuan Yue School of Electrical Engineering and Information of Sichuan University 2684437602@qq.com 
Zhang Zhiqiang School of Electrical Engineering and Information of Sichuan University 1926127794@qq.com 
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中文摘要:
      如何有效减少配电网重构中不可行解的产生是提高搜索速度的重要环节。为提高搜索效率,在对网络进行拓扑简化的基础上,提出一种基于环路矩阵分块重组策略的配电网重构预处理方法,实现了解空间压缩与分解。结合该策略,以布谷鸟搜索算法及其改进算法为例对IEEE33节点系统和119节点系统进行了算例仿真,结果表明结合环路矩阵分块重组策略后能够有效避免不可行解的产生,算法只在少数可行范围内进行搜索,搜索范围减少,计算速度与寻优成功率显著提高,验证了提出策略的有效性;最后将此策略运用于多种智能算法,对比结果表明该策略能使算法在性能上得到显著提升,验证了所提策略的适用性。
英文摘要:
      How to effectively reduce the generation of infeasible solutions in distribution network reconstruction is an important step to improve the search speed. To improve search efficiency, on the basis of simplification of the network topology,an pretreatment method based on loop matrix block-recombination strategy is presented which could compress and resolve the solution space. Combined with this strategy,simulation is performed in Cuckoo Search method and its improved method on IEEE33 node system 119 node system and the results show the analytical method based on loop matrix block-recombination can effectively avoid the generation of infeasible solutions. The algorithm only searches within a few feasible ranges so the search area is reduced.And the algorithm is faster and is of greater success rate of solving, then the validity of the proposed model is verified. Finally, this strategy is applied to a variety of intelligent algorithms. The results show that this strategy can significantly improve the performance of the algorithm then the applicability of the proposed strategy is verified.
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