摘要
故障区段定位对于配电网发生故障后的故障处理与供电恢复具有重要意义。有源配电网故障定位方法中,矩阵算法计算速度快但容错性差,智能优化算法容错性高但定位速度慢且在大规模配电网中存在局部收敛的问题,在此背景下提出将矩阵算法和智能优化算法优点相结合的定位方法。首先,在有源配电网发生故障后,利用馈线终端(FTU)上传的告警信息,运用矩阵算法快速定位故障区段。然后,运用开关函数对矩阵算法的定位结果进行校验,避免因矩阵算法容错性差而输出错误的定位结果。校验不通过的定位结果将全部列入可疑故障集合,该集合的维度大幅低于配电网的维度,再运用灰狼优化(GWO)算法对该集合进行优化处理,从而输出最终的定位结果。最后,在Matlab上进行仿真测试,结果表明所提方法能实现有源配电网中故障区段的快速定位,且具有一定的容错性。
Fault location is of great significance for fault handling and power restoration of distribution network.In the fault location method for active distribution network,the calculation speed of matrix algorithm is high,but this method has a poor fault tolerance.The fault tolerance of intelligent optimization algorithm is strong,but this method has local convergence problems in large-scale distribution network,and it has a low speed.To solve the problems above,a comprehensive approach for the fault location in distribution network which combines the advantages of both methods is proposed.Firstly,the matrix algorithm is used to locate the fault section rapidly after fault occurs in active distribution network,which uses the alarm information uploaded by the feeder terminal unit(FTU).Then,in order to avoid outputting wrong positioning results caused by poor fault tolerance of matrix algorithm,the positioning results of matrix algorithm is verified by switching function.The location results that fail the verification is included in the suspicious fault set whose dimension is much lower than that of the distribution network.To output the final positioning results,the grey wolf optimization(GWO)algorithm is used to optimize the set above.Finally,the simulation tested by Matlab shows that the proposed method can achieve fault location rapidly with strong fault tolerance in active distribution network.
作者
梅飞
陈子平
裴鑫
郑建勇
MEI Fei;CHEN Ziping;PEI Xin;ZHENG Jianyong(College of Energy and Electrical Engineering,Hohai University,Nanjing 211100,China;School of Electrical Engineering,Southeast University,Nanjing 210096,China)
出处
《电力工程技术》
北大核心
2022年第6期109-115,共7页
Electric Power Engineering Technology
基金
江苏省重点研发计划资助项目(BE2020027)。
关键词
有源配电网
故障定位
矩阵算法
容错性
信息校验
灰狼优化(GWO)算法
active distribution network
fault location
matrix algorithm
fault tolerance
information verification
grey wolf optimization(GWO)algorithm
