摘要
阐述电网系统运行中存在的非线性参数,影响对故障的识别和准确定位。以蚁群算法为基础,引入遗传算法的交叉、变异操作,建立一种改进的蚁群遗传算法进行输变电线路的运行监控和故障识别定位。算法根据前期遗留信息素获得初始有效路径,对系统中存在的非线性干扰信号可能造成寻优中断,采用遗传算法的交叉、变异运算,获得目标函数的最大路径,选择适应度函数来选取候选解,进行算法迭代运算,得到路径最优解。基于Matlab软件建立超高压输变电系统的故障仿真表明,算法的故障识别准确,故障定位相对误差控制在0.1%以下,故障识别和定位都能取得很好的测量精度。
It is difficult to identify and locate the faults of power grid system.Based on the ant colony algorithm, we introduce the crossover and variant operation of the genetic algorithm, and an improved ant colony genetic algorithm is established for the operation monitoring and fault identification positioning of transmission lines. The algorithm obtains the initial effective path according to the early stage, and the nonlinear interference signal existing in the system may cause optimal interruption. The genetic algorithm can obtain the maximum path of the target function, select the fitness function to select the candidate solutions, perform the algorithm iteration operation, and obtain the optimal path solution.The short circuit fault simulation of ultra-high voltage transmission line through Maylab software shows that the fault identification of the algorithm is accurate, the relative error of fault positioning is controlled below 0.1%, and the fault identification and positioning can achieve good measurement accuracy.
作者
任晓龙
孙红宝
赵世慧
陈曦
黄文礼
REN Xiaolong;SUN Hongbao;ZHAO Shihui;CHEN Xi;HUANG Wenli(State Grid Shaanxi Xintong Company,Shaanxi 710065,China;State Grid Shaanxi Electric Power Co.,Ltd.,Shaanxi 710048,China;Anhui NARI Jiyuan Power Grid Technology Co.,Ltd.,Anhui 230601,China)
出处
《电子技术（上海）》
2022年第9期64-67,共4页
Electronic Technology
关键词
蚁群算法
交叉变异
输电线路
电网故障
ant colony algorithm
cross variation
transmission lines
power grid failure
