Open AccessResearch on Intelligent Detection Technology of Short-term Flashover Fault in High-Power Main Network Power Systems
Author(s) -
Ding Yi-min,
Hai Jin,
Ming Fan
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 - 10.1088/1742-6596/1345/5/052044
Subject(s) - fault (geology) , electric power system , wavelet , power network , power (physics) , fault detection and isolation , network packet , term (time) , computer science , fault indicator , engineering , real time computing , reliability engineering , artificial intelligence , computer network , physics , quantum mechanics , seismology , actuator , geology
Traditional detection techniques are affected by surrounding factors and cannot accurately determine the location of the fault point. In order to solve the problem, a short-term flashover fault intelligent detection method in the paper is proposed for high-power main network power system. The short-term flashover fault feature of the high-power main network power system is extracted by the wavelet-type wavelet packet energy moment. The CPRS networking mode is used to intelligently detect the short-term flashover fault of the high-power main network power system. Experiments show that the proposed technique is more accurate than traditional detection techniques.