摘要
分布式电源的大量接入使传统的故障定位方法对复杂规模化的有源配电网不再适应。针对此问题,提出一种基于自适应遗传粒子群算法实现有源配电网的故障区间定位。构造了一种适用于有源配电网的整数规划模型,根据馈线终端设备上传的过电流信息,将复杂的配电网故障信息转化为由整数表述的故障向量;计及分布式发电出力的不确定性,构建了新的开关函数和评价函数,利用自适应遗传粒子群算法根据转化后的故障向量应用于有源配电网的故障区段定位。通过Matlab进行仿真测试,结果表明:基于自适应遗传粒子群算法的有源配电网故障定位方法能提高故障区段定位的准确度与算法收敛速度,同时对畸变信息具有高容错性。
With the massive access of the Distributed Generator,the traditional fault location method is no longer suitable for the complex large-scale active distribution network.To solve this problem,a hybrid algorithm based on adaptive genetic particle swarm optimization is proposed to realize fault location in active distribution networks.Firstly,according to the characteristics of adaptive genetic algorithm and adaptive particle swarm optimization,a hybrid adaptive genetic particle swarm optimization algorithm is proposed.Secondly,an integer programming model suitable for active distribution network is constructed.According to the overcurrent information uploaded by feeder terminal equipment,the complex fault information of distribution network can be transformed into fault vector expressed by integer.At the same time,considering the uncertainty of distributed generation output,a new switching function and evaluation function are constructed,and the hybrid algorithm is applied to the fault location of active distribution network based on the converted fault vector.Finally,the simulation test by Matlab shows that the fault location method based on the hybrid algorithm of adaptive genetic particle swarm optimization can effectively improve the accuracy of fault location and the convergence speed of the algorithm,and at the same time has a high fault tolerance to distortion information.
作者
张莲
宫宇
杨洪杰
李涛
赵梦琪
张尚德
贾浩
ZHANG Lian;GONG Yu;YANG Hongjie;LI Tao;ZHAO Mengqi;ZHANG Shangde;JIA Hao(Chongqing Energy Internet Engineering Technology Research Center, Chongqing 400054, China;School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing 400054, China)
出处
《重庆理工大学学报（自然科学）》
北大核心
2021年第9期160-168,共9页
Journal of Chongqing University of Technology：Natural Science
关键词
有源配电网
自适应遗传算法
自适应粒子群算法
故障区段定位
整数规划模型
active distribution network
adaptive genetic algorithm
adaptive particle swarm optimization
fault range location
integer programming mode
