基于人工鱼群算法的配电网故障定位  

Fault location of distribution network based on artificial fish swarm algorithm

作　　者：陈磊[1,2,3] 詹跃东[1] 田庆生 Chen Lei;Zhan Yuedong;Tian Qingsheng(Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China;Kunming University of Science and Technoiogy's Postgraduate Workstation of Yunnan Power Grid Company,Kunming 650217,China;Yunnan Electric Power Research Institute (Group)Co.,Ltd.,Kunming 650217,China)

机构地区：[1]昆明理工大学信息工程与自动化学院,昆明650500 [2]昆明理工大学云南电网有限责任公司电力科学研究院研究生工作站,昆明650217 [3]云南电力试验研究院(集团)有限公司,昆明650217

出　　处：《电子测量技术》2018年第23期1-5,共5页Electronic Measurement Technology

基　　金：国家自然科学基金(51667012)项目资助

摘　　要：配电网故障定位根据故障指示器上报信息来判断故障区段,主站需高效处理上报的大量故障信息来判断故障位置,因此需要算法来迅速准确地处理故障信息。鉴于人工鱼群算法具备较好的全局寻优能力,能迅速跳出局部最优点。基于人工鱼群算法,依据安装在配网线路上的故障指示器上报线路故障与否,提出二进制编码规则,结合大理供电局某10 kV线路故障线路的实际情况,运用MATLAB软件进行模拟仿真。通过分析仿真结果表明,人工鱼群算法在配电网线路故障定位方面依据故障指示器的上报信息,可以准确地缩小故障位置的范围,准确率达到90%左右,具有较好的工程实用性。The fault location of the distribution network is judged according to the information of the fault indicator to judge the fault section. The main station needs to deal with the large number of fault information in the report to judge the fault location, so the algorithm is needed to deal with the fault information quickly and accurately. In view of the fact that the artificial fish swarm algorithm has better global optimization capability, it can quickly jump out of the local optimum. Based on artificial fish swarm algorithm, this paper puts forward binary coding rules for fault indicator reporting fault or not, and uses MATLAB software to simulate the actual situation of a 10 kV line fault line in Dali Power Supply Bureau. Through the analysis of the simulation results, it shows that the artificial fish swarm algorithm can reduce the range of the fault location in the distribution network fault location, the Locating fault speed is fast, the accuracy rate is up to 90%, and it has a good engineering practicality.

关 键 词：配电网 故障定位 二进制编码 人工鱼群算法 准确率高 

分 类 号：TN7[电子电信—电路与系统]