Power Grid Fault Positioning Technology based on Particle Swarm Optimization

被引：0
|
作者：
Tang Rongbo [1 ]
机构：
[1] Chongqing Tech Coll Water Resources & Elect Engn, Chongqing 402160, Peoples R China
来源：
2014 SIXTH INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION (ICMTMA) | 2014年
关键词：
Power Grid; Fault Positioning; immune particle swarm optimization; CURRENT LIMITING TRANSFORMER; REFLECTOMETRY;
D O I：
10.1109/ICMTMA.2014.111
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Using the transient fault signal to realize the power grid fault location is a hotspot, which plays an important role in rapid recovery of power grid. This paper studies the principle of the wavelet neural network. Because wavelet neural network is easy to fall into local optimum and has the disadvantage of slow convergence rate, it is improved by immune particle swarm algorithm. The improved algorithm is applied to grid fault positioning, and the results show that the accuracy of improved algorithm is obviously superior to accuracy of wavelet neural network. It can provide important reference for the actual power grid fault positioning system.
引用
收藏
页码：301 / 304
页数：4
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