Research on Analysis of Power System Transient Signal by Neural Network and Genetic Algorithm

被引：0
作者：
Guo Liang-kun [1 ]
Yang Xuan-fang [1 ]
Wang Jia-lin [1 ]
机构：
[1] Naval Univ Engn, Coll Elect Engn, Wuhan, Peoples R China
来源：
PROCEEDINGS OF 2020 IEEE 4TH INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2020) | 2020年
基金：
中国国家自然科学基金;
关键词：
neural network; genetic algorithm; power system; transient signal analysis;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
It is an important and difficult subject to acquire accurate transient signal parameters in the field of power system signal analysis. A neural network combined with genetic algorithm analysis approach for power system transient signal is proposed to improve the analysis precision of the transient signal including a period component varying in spectral waveform, a non-period component varying in exponential waveform and switching operation sequence. The signal parameters which are assembly estimated based on numeric differential and genetic algorithm are used as initial value of the neural network. The fundamental frequency is treated as weight to be adjusted to estimate the signal frequency and all harmonics' amplitudes and phases. The learning rate and the delayed frequency adjustment improve the convergence performance. The result of Matlab simulation demonstrates that the algorithm achieved high accuracy and rapid convergence.
引用
收藏
页码：903 / 907
页数：5
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