Study of a New Approach about Locating Single-phase-to-ground Fault

DOI

10.2991/eeic-13.2013.83How to use a DOI?

Keywords

single phase grounding fault; wavelet transformation; optimized back-propagation network; genetic algorithm; fault location;

Abstract

First this paper briefly analyzes the electric power transient signal of single phase grounding fault, and then the fault characteristics of zero sequence current and bus voltage is obtained by wavelet transformation. Finally by using genetic algorithm to optimize the original weights of back-propagation neural network, as well as taking the fault characteristics as the input characteristic vector of optimized back propagation neural network, the network is trained and tested. The simulation result shows that the prediction effects and convergence rate of optimized back-propagation network have better performance than traditional back-propagation network. It’s relatively error were less than 3%, independent of fault distance, power supply phase angle and the impact of transient resistance.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Bing Jiang
AU  - Chuan Zang
AU  - Zhiguo Xiao
AU  - Jie Yin
PY  - 2013/12
DA  - 2013/12
TI  - Study of a New Approach about Locating Single-phase-to-ground Fault
BT  - Proceedings of the 3rd International Conference on Electric and Electronics
PB  - Atlantis Press
SP  - 355
EP  - 359
SN  - 1951-6851
UR  - https://doi.org/10.2991/eeic-13.2013.83
DO  - 10.2991/eeic-13.2013.83
ID  - Jiang2013/12
ER  -