• 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