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

Abstract:

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.

• Periodical: Applied Mechanics and Materials (Volumes 325-326)
• Pages: 565-568
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.325-326.565
• Online since: June 2013
• Authors: Yu Sheng Zhou, Yong Feng Liu, Xiang Jun, Zheng Pan
• Keywords: Extreme Learning Machine (ELM), Fault Line Selection, Ground Fault, Information Fusion, Morphological Filtering

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