基于模拟退火的粒子群算法的配电网区间故障定位研究  

Research on distribution network interval fault location based on simulated annealing particle swarm optimization

作　　者：曹鲁成 何晋[1] 赵太彪 Cao Lucheng;He Jin;Zhao Taibiao(School of Electrical Information Engineering,Yunnan Min Zu University,Kuming 650000,China;State Grid Gansu Electric Power Company Zhangye Power Supply Company,Zhangye 734000,China)

机构地区：[1]云南民族大学电气信息工程学院,昆明650000 [2]国网甘肃省电力公司张掖供电公司,张掖734000

出　　处：《电子测量技术》2019年第23期169-172,共4页Electronic Measurement Technology

基　　金：国家自然科学基金(61365007)项目资助

摘　　要：目前配电网的区间故障定位技术,已有少部分应用于市场上,但是仍然有着很多技术问题,其中比较重要的一个问题就是由于现场设备上传至控制中心的故障信息出现信息丢失时造成的矩阵法无法准确判断的问题,虽然使用人工智能算法可以解决此类问题,但是在配电网故障定位算法中以粒子群为代表的人工智能算法存在容易陷入局部最优陷阱等问题。针对此问题,提出基于模拟退火的粒子群算法的配电网区间故障定位算法,并通过仿真验证了该算法的可行性,结果表明该算法能够精确判断出在配电网中出现的单点及多点故障时的区间位置,并且在现场设备上传信息有缺失的情况下仍然可以得出正确的结果,容错性能和收敛性能优越。At present,the interval fault location technology of distribution network has been applied in the market,but there are still many technical problems.One of the more important problems is that the matrix method can not accurately judge the information loss caused by the fault information uploaded from field equipment to the control center.Although artificial intelligence algorithm can solve such problems,it still has many technical problems.The artificial intelligence algorithm represented by particle swarm optimization(PSO)is easy to fall into the trap of local optimum in distribution network fault location.In order to solve this problem,this paper proposes an interval fault location algorithm based on simulated annealing particle swarm optimization,and verifies the feasibility of the algorithm through simulation.The results show that the algorithm can accurately determine the interval location of single point and multi-point faults in distribution network,and can still get the correct results when the upload information of field equipment is missing.The performance of fault tolerance and convergence is superior.

关 键 词：配电网 区间故障定位 局部最优陷阱 基于模拟退火的粒子群算法 容错性能 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]