电力系统及其自动化学报2025，Vol.37Issue(5)：141-148,158,9.DOI:10.19635/j.cnki.csu-epsa.001501
基于灰狼-粒子群算法的有源配电网故障定位
Fault Location of Active Distribution Network Based on GWO-PSO Algorithm
摘要
Abstract
Aimed at the issue that the particle swarm optimization(PSO)algorithm is prone to fall into local optimum and its convergence speed is slow when solving the fault localization problem of active distribution network,a grey wolf optimizer-PSO(GWO-PSO)fault location algorithm for active distribution network is studied based on the hierarchical population system of GWO.This algorithm utilizes the hierarchical system of GWO instead of the optimal individual in the PSO algorithm,and the guidance by the hierarchical population makes the modified PSO algorithm not easy to fall into the local optimum.At the same time,combined with the hierarchical convergence factor of GWO,the PSO algo-rithm adjusts the allocation of global optimization and local accurate optimization in different iteration periods,thus im-proving its convergence speed.Based on an IEEE 33-node distribution network model,the numerical analysis of the GWO-PSO fault localization algorithm for active distribution network is given,and results show that the GWO-PSO algo-rithm has advantages in terms of convergence speed and localization accuracy.关键词
有源配电网/故障定位/粒子群优化算法/灰狼优化算法/等级制度Key words
active distribution network/fault location/particle swarm optimization(PSO)algorithm/grey wolf optimiz-er(GWO)algorithm/hierarchical system分类
信息技术与安全科学引用本文复制引用
熊芮,赵林军,张宇航..基于灰狼-粒子群算法的有源配电网故障定位[J].电力系统及其自动化学报,2025,37(5):141-148,158,9.基金项目
陕西省自然科学基金资助项目(2023-JC-YB-442). （2023-JC-YB-442）
