基于鲸鱼优化算法的配电网故障区段定位  

Fault localization of distribution network based on whale optimization algorithm

作　　者：张荣升 刘丽桑[1] 宋天文[1] 邓慧琼[1] 李培强[1] 郑荣进[1] ZHANG Rongsheng;LIU Lisang;SONG Tianwen;DENG Huiqiong;LI Peiqiang;ZHENG Rongjin(School of Electronic,Electrical Engineering and Physics,Fujian University of Technology,Fuzhou 350118,China)

机构地区：[1]福建工程学院电子电气与物理学院,福建福州350118

出　　处：《福建工程学院学报》2021年第4期378-384,共7页Journal of Fujian University of Technology

基　　金：福建省科技厅面上项目(2019J01773);福建工程学院校级科研发展基金(GY-Z18183)。

摘　　要：为提高配电网络中故障区段定位的准确性和高效性,基于馈线终端单元的配电网区段定位的研究,提出了一种在含分布式电源的配电网中用鲸鱼优化算法实现故障区段定位的方法。通过MATLAB对支路矩阵、电源接入情况进行编程,创建含多电源的IEEE33节点的配电网模型,完成配电网故障信息编码方式、开关函数和适应度函数的构造。对发生单点故障、多点故障,以及存在信息畸变的情况下发生故障的定位结果分析,结果表明,提出的鲸鱼算法能实现准确定位,其收敛性、准确性和高效性均优于传统粒子群算法、遗传算法以及最近的蝠鲼觅食算法。In order to improve the accuracy and efficiency of fault location in the distribution network,based on the research on the localization of feeder terminal units in the distribution network,a method of applying whale optimization algorithm to locate fault sections in the distribution network with distributed power supply was proposed.The branch matrix and power access were programmed by MATLAB,and the IEEE33-node distribution network model with multiple power sources was created.Then,the coding mode,switching function and fitness function of distribution network fault information were constructed.The localization results of single point fault,multi-point fault and information distortion were analyzed,and the results show that the whale algorithm can achieve accurate location.The whale optimization algorithm is higher than the traditional particle swarm optimization algorithm,genetic algorithm and the recently proposed manta ray foraging algorithm in convergence,accuracy and algorithm efficiency.

关 键 词：配电网 馈线终端单元 分布式电源 故障区段定位 鲸鱼优化算法 

分 类 号：TM7[电气工程—电力系统及自动化]