Based on genetic algorithm to optimize learn vector quantization neural network is a new algorithm of distribution network fault line selection

2014 ◽  
Author(s):  
Yusheng Zhou ◽  
Pai Peng ◽  
Yunlong Gao ◽  
Zhengzhou An ◽  
Rangjiao Liu
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Vector Quantization ◽  
Distribution Network ◽  
Fault Line ◽  
Fault Line Selection ◽  
Line Selection ◽  
Network Fault

Single-phase-to-ground fault line selection and location technology in distribution network based on signal similarity

2021 ◽  
Author(s):  
Xinyu Zhang ◽  
Yang Wang ◽  
Zenghao Liu ◽  
Wei Du ◽  
Xiaoxiao Hu ◽  
...  
Keyword(s):  
Single Phase ◽  
Distribution Network ◽  
Fault Line ◽  
Fault Line Selection ◽  
Ground Fault ◽  
Line Selection ◽  
Signal Similarity

Grounding Failure Detection Based on ELM Information Fusion in Distribution Power Systems

2013 ◽  
Vol 325-326 ◽  
pp. 565-568
Author(s):  
Yu Sheng Zhou ◽  
Yong Feng Liu ◽  
Xiang Jun ◽  
Zheng Pan
Keyword(s):  
Power Systems ◽  
Information Fusion ◽  
Information Integration ◽  
Single Phase ◽  
Wavelet Packet ◽  
Distribution Network ◽  
Failure Detection ◽  
Fault Line ◽  
Fault Line Selection ◽  
Line Selection

For the complexity of the distribution network and the particularity of single-phase grounding fault, intelligent distribution network grounding fault line selection model based on the Extreme Learning Machine (ELM) information integration is proposed in the paper. When a single-phase grounding fault happened, the relation functions for the wavelet packet decomposition, the fifth harmonic method and the traveling wave method are respectively determined, the fault estimate data of transient zero-sequence current are calculated. The fault line is accurately judged by the ELM networks information fusion. Through analyzing MATLAB simulation result about different ground fault line selection, the validity and accuracy of the method are verified.

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