Open AccessDiagnosis of the single phase‐to‐ground fault in distribution network based on feature extraction and transformation from the waveforms
Author(s) -
Shi Fang,
Zhang Linlin,
Zhang Hengxu,
Xu Kai,
Vladimir Terzija
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2020.0877
Subject(s) - transformation (genetics) , fault (geology) , waveform , phase (matter) , extraction (chemistry) , feature (linguistics) , feature extraction , distribution (mathematics) , computer science , pattern recognition (psychology) , artificial intelligence , physics , mathematics , geology , seismology , telecommunications , mathematical analysis , chemistry , philosophy , chromatography , biochemistry , linguistics , quantum mechanics , gene , radar
The increasing permeation of the distributed generators in the power system brings great challenges for fault diagnosis, especially for the distribution networks with ungrounded neutral or grounded by Peterson coil as the fault current is limited and easily affected by the noises and interferences. A single phase‐to‐ground fault section identification method is proposed based on feature extraction of the synchronous waveforms and the calculation of the eigenvalues for the time‐sequenced features. First, several fault features are defined and extracted from the synchronous current waveforms obtained by the fault recorders. Then, the topology related fault feature matrix is constructed using the time‐series features obtained from different measurement sites, and the eigenvalues of the matrix are calculated based on the random matrix theory. Lastly, using the distribution characteristics of the eigenvalues, improved K ‐means clustering algorithm is utilised in classifying the fault cases and identifying the faulty sections. The effectiveness of the proposed scheme is verified by IEEE 34 nodes test system and a multi‐feeder distribution network.