发电技术2025，Vol.46Issue(2)：231-239,9.DOI:10.12096/j.2096-4528.pgt.24242
基于改进二进制粒子群优化算法的综合能源系统故障定位研究
Research on Fault Location in Integrated Energy Systems Based on Improved Binary Particle Swarm Optimization Algorithm
摘要
Abstract
[Objectives]The coverage of power systems continues to expand,and the structure of integrated energy systems is becoming increasingly complex.This trend leads to a significant decline in the accuracy of fault location in the distribution network that is a critical component of the energy system.To address this,a fault location method for distribution network based on an improved binary particle swarm optimization(BPSO)algorithm is proposed.[Methods]During each iteration of the binary particles,an adaptive mutation operation is first performed on the position of the particle.Furthermore,an adaptive method is introduced into the setting of inertia weight,establishing a BPSO algorithm with dual adaptive characteristics.[Results]In the standard radial distribution networks and those incorporating distributed generation,the improved BPSO algorithm can accurately pinpoint fault sections.[Conclusions]Compared with the traditional BPSO algorithm and genetic algorithm,the improved algorithm demonstrates stronger robustness in convergence ability.It remains unaffected by differences in fault types and has greater reliability.Therefore,it is more suitable for fault location tasks in complex and dynamic distribution network environments.关键词
综合能源/配电网/故障定位/分布式电源/二进制粒子群优化(BPSO)算法/双重自适应Key words
integrated energy/distribution network/fault location/distributed generation/binary particle swarm optimization(BPSO)algorithm/dual adaptive分类
能源与动力引用本文复制引用
赵睿智,练小林,应凯文,柳杰,李丝雨,高扬..基于改进二进制粒子群优化算法的综合能源系统故障定位研究[J].发电技术,2025,46(2):231-239,9.基金项目
国网上海市电力公司科技项目(5209KZ240003).Project Supported by State Grid Shanghai Electric Power Company Technology Project(5209KZ240003). （5209KZ240003）
