电子器件2025，Vol.48Issue(2)：414-419,6.DOI:10.3969/j.issn.1005-9490.2025.02.027
基于图论和遗传优化算法的自愈型配电网馈线重构
Reconfiguration of Self-Healing Distribution Network Feeders Based on Graph Theory and Genetic Optimization Algorithm
摘要
Abstract
By changing the topology of the distribution network,interference propagation and cascading events can be effectively stopped,thus enhancing the self-healing capability of the distribution network and enabling faster recovery of the distribution system in the event of a fault.To address the failure of self-healing methods,a graph-theoretic distribution system reconfiguration strategy is devel-oped.This method maximizes the amount of load to be recovered and minimizes the number of switching operations.By modeling the distribution system as a virtual feeder and representing it as a spanning tree,a genetic optimization algorithm is used to find candidate recovery strategies.To ensure that the proposed system topology can meet the actual electrical operating constraints,unbalanced three-phase power flows are calculated for the system.Experimental results on the IEEE-33 node standard distribution network show a 31.2%reduction in active power loss and a 7.73%increase in voltage compared to the initial configuration.关键词
自愈/配电系统重构/生成树/遗传优化Key words
self-healing/distribution system reconfiguration/spanning tree/genetic optimization分类
信息技术与安全科学引用本文复制引用
潘凯岩,赵瑞锋,刘海信,卢建刚,郭文鑫,刘宏达..基于图论和遗传优化算法的自愈型配电网馈线重构[J].电子器件,2025,48(2):414-419,6.基金项目
南方电网科技项目(030400KK52190115) （030400KK52190115）
