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基于ICOA-IEM算法的含分布式电源配电网分区故障定位

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针对分布式电源大量接入使得配电网结构复杂化,导致故障定位难度增大的问题,本文提出一种改进黑猩猩算法与隐枚举法结合的配电网分区故障定位方法。首先,引入Iteration映射来提高初始化种群质量,加入变异柯西算子和反向学习策略以及单纯形法用于改善算法的局部开发能力和勘探能力;然后,建立含分布式电源的开关函数和目标函数,依据故障点与开关函数的对应机理,进行区域划分;最后,通过仿真验证,所提方法与传统的黑猩猩算法分区定位方法相比在求解速度上平均提高43。05%,准确率上平均提高1。17%,表明改进黑猩猩分区定位方法能够准确、迅速定位故障区段,同时具有较高的容错性。
Fault Location of a Distribution Network Hierarchical Model with a Distribution Generator Based on ICOA-IEM
The large-scale integration of distributed power sources complicates the structure of the distribution network,resulting in increased difficulty in fault localization.A distribution network partition fault location method with improved chimpanzee algorithm is proposed.Firstly,Iteration mapping is introduced to improve the initialized population quality,and then Cauchy variation and backward learning strategy as well as simplex method are added to improve the local exploitation capability and exploration capability of the algorithm.The switching function and objective function containing distributed power supply are established,and the region is divided according to the correspondence mechanism between the fault point and the switching function.Finally,it is verified by simulation that the proposed method improves the solution speed by 43.05%on average and the accuracy by 1.17%on average compared with the traditional chimpanzee algorithm partitioning localization method.It is shown that the method can accurately and rapidly locate the faulty zones with high fault tolerance.

distribution generatordistribution networkfault locationsubregionimproved chimpanzee algorithm

吴艺、文中、冯铃、覃治银、郑连华、汤伟钊

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三峡大学电气与新能源学院,湖北宜昌 443002

分布式电源 配电网 故障定位 分区 改进黑猩猩算法

国家自然科学基金

51807110

2024

广西师范大学学报(自然科学版)
广西师范大学

广西师范大学学报(自然科学版)

CSTPCD北大核心
影响因子:0.448
ISSN:1001-6600
年,卷(期):2024.42(4)