Open AccessFault diagnosis of power grids based on grey relational analysis
Author(s) -
Huayong Lu,
Hongzuo Guo,
Zhe Liu,
Yang Xiao,
Bing Leng
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1303/1/012088
Subject(s) - grey relational analysis , fault (geology) , degree (music) , line (geometry) , relation (database) , computer science , sampling (signal processing) , electric power system , power (physics) , data mining , reliability engineering , mathematics , engineering , statistics , geometry , geology , computer vision , physics , filter (signal processing) , quantum mechanics , seismology , acoustics
A fault diagnosis method of power grids was presented based on grey relational analysis in this paper. For each suspected fault line in the power cut area, the grey relational of original characteristics sequence, amplitude and energy are calculated by using the current sampling value before and after the fault time. Then an active reference line was selected, followed by the calculation of the horizontal grey correlation between reference line and suspected fault line according to current sampling after the fault. Finally, the longitudinal grey relational degree and the horizontal grey relational degree of each line are weighted and fused to obtain their comprehensive grey relational degree, and the fault criterion is given to identify the faulty component accurately. The simulation results of the IEEE 14-node system show that the fault elements can be identified under different fault locations, various fault types and different transition resistances accurately.