DocumentCode :
3608813
Title :
An overview of state-of-the-art partial discharge analysis techniques for condition monitoring
Author :
Min Wu ; Hong Cao ; Jianneng Cao ; Hai-Long Nguyen ; Gomes, Joao Bartolo ; Krishnaswamy, Shonali Priyadarsini
Author_Institution :
Data Analytics Dept., Inst. for Infocomm Res., Singapore, Singapore
Volume :
31
Issue :
6
fYear :
2015
Firstpage :
22
Lastpage :
35
Abstract :
As one step toward the future smart grid, condition monitoring is important to facilitate the reliability of grid asset operation and to save on maintenance cost [1]. Most failures of the power grid are caused by electrical insulation failure, and a key indicator of such electrical failure is the occurrence of partial discharge (PD). Therefore, one focus of condition monitoring is to detect PD, especially in the early stages, to prevent a serious power failure or outage.
Keywords :
condition monitoring; insulation; partial discharges; power system reliability; smart power grids; Condition Monitoring; PD; electrical insulation failure; power failure; smart grid reliability; state-of-the-art partial discharge analysis technique; Acoustic sensors; Current transformers; Discharges (electric); Feature extraction; Oil insulation; Partial discharges; Power transformer insulation; condition monitoring; feature extraction; partial discharge; pattern recognition; sensor;
fLanguage :
English
Journal_Title :
Electrical Insulation Magazine, IEEE
Publisher :
ieee
ISSN :
0883-7554
Type :
jour
DOI :
10.1109/MEI.2015.7303259
Filename :
7303259
Link To Document :
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