摘要
针对电力输电线路故障分布式感知精度问题,提出一种基于行波时差关系与BAS-CPSO的故障定位算法。首先引入天牛须算法对混沌粒子群算法进行改进,以提高混沌粒子群算法的寻优性能;然后根据输电线路故障的行波时差关系,利用BAS-CPSO算法对故障进行准确定位。测试结果表明,引入天牛须算法改进的混沌粒子群算法,相较于SPSO、CPSO、BASPSO等主流搜索算法具有更好的搜索性能,在测试函数中表现出较高的收敛精度与搜索速度,寻优效果更好。在对电网输电系统的仿真实验中,所提基于行波时差关系与BAS-CPSO的定位算法对所有线路的故障定位绝对误差都在100 m以内,远远小于300 m的实际输电线路故障定位精度要求;在同一仿真条件下,所提定位算法的定位误差相较于双端定位法、传统网络定位法降低了81.66%和45.92%,定位精度较高,值得进一步研究推广。
To solve the problem of distributed fault sensing accuracy of power transmission lines,a fault location algorithm based on travelling wave time difference and BAS-CPSO is proposed.Firstly,the Tianniu algorithm is introduced to improve the chaotic particle swarm optimization algorithm,so as to improve the optimization performance of chaotic particle swarm optimization algorithm.Then BAS-CPSO algorithm is used to locate the fault accurately according to the traveling wave time difference of transmission line fault.The test results show that compared with the mainstream search algorithms such as SPSO,CPSO and BASPSO,the chaotic particle swarm optimization algorithm introduced by the Tianusu algorithm has better search performance,higher convergence accuracy and search speed in the test function,and better optimization effect.In the simulation experiment of power grid transmission system,the absolute error of fault location for all lines of the proposed algorithm based on traveling wave time difference relationship and BAS-CPSO is less than 100m,which is far less than 300m of actual transmission line fault location accuracy.Under the same simulation condition,the positioning error of the proposed positioning algorithm is reduced by 81.66%and 45.92%compared with the two-end positioning method and the traditional network positioning method,and the positioning accuracy is high,which is worthy of further research and popularization.
作者
庄梦珂
唐卓
黄凤
何娟
郑高珊
ZHUANG Meng Ke;ZHUO Tang;FENG Huang;JUAN He;ZHENG Gaoshan(State Grid Sichuan Economic Research Institute,Chengdu 610041,China;State Grid Sichuan Yibin Electric Power Supply Company,Yibin Sichuan 644000,China;State Grid Sichuan Deyang Electric Power Supply Company,Deyang Sichuan 618000,China;Beijing Guodiantong Network Technology Co.,Ltd.,Beijing 100071,China)
出处
《自动化与仪器仪表》
2024年第2期96-100,共5页
Automation & Instrumentation
基金
《基于云数平台的线网智能运维技术研究》(XD-JY-2022063)。
关键词
粒子群算法
天牛须算法
输电线路
故障定位
分布式感知
particle swarm optimization
beetle antennae search
transmission lines
fault location
distributed perception
