Application of improved PSO algorithm in power grid fault diagnosis

被引：0
|
作者：
Bian li [1 ]
Duan Yingli [2 ]
Liu Penghua [3 ]
机构：
[1] Guangdong Ocean Univ, Coll Elect & Informat Engn, Zhanjiang 524088, Guangdong, Peoples R China
[2] Heilongjiang Univ Sci & Technol, Sch Elect & Control Engn, Harbin 150022, Peoples R China
[3] State Grid Henan Elect Power DC Management Off, Zhumadian 454000, Henan, Peoples R China
来源：
2020 ZOOMING INNOVATION IN CONSUMER TECHNOLOGIES CONFERENCE (ZINC) | 2020年
关键词：
Fault diagnosis; Particle swarm optimization; 0-1 integer programming;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This paper proposes a method to improve the weight of Particle swarm optimization (PSO) by using similarity, so as to realize the fast and accurate diagnosis of power grid fault. First, a mathematical model of power grid fault diagnosis is established by analyzing the circuit breaker, equipment protection and action information in the power grid. Next, the model is transformed into a 0-1 integer programming problem. Last, the traditional PSO algorithm is improved, so that the inertia weight in the algorithm can be adjusted dynamically according to the concept of similarity. Simulation results show that the improved PSO greatly increases the convergence speed and efficiency of power grid fault diagnosis.
引用
收藏
页码：242 / 247
页数：6
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