• DocumentCode
    1238404
  • Title

    Automatic Classification and Characterization of Power Quality Events

  • Author

    Gargoom, Ameen M. ; Ertugrul, Nesimi ; Soong, Wen L.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Adelaide Univ., Adelaide, SA
  • Volume
    23
  • Issue
    4
  • fYear
    2008
  • Firstpage
    2417
  • Lastpage
    2425
  • Abstract
    This paper presents a new technique for automatic monitoring of power quality events, which is based on the multiresolution S-transform and Parseval´s theorem. In the proposed technique, the S-transform is used to produce instantaneous frequency vectors of the signals, and then the energies of these vectors, based on the Parseval´s theorem, are utilized for automatically monitoring and classification of power quality events. The advantage of the proposed algorithm is its ability to distinguish different power quality classes easily. In addition, the magnitude, duration, and frequency content of the disturbances can be accurately identified in order to characterize the disturbances. The paper provides the theoretical background of the technique and presents a wide range of analyses to demonstrate its effectiveness.
  • Keywords
    power supply quality; power system measurement; transforms; Parseval theorem; automatic monitoring; instantaneous frequency vectors; multiresolution S-transform; power quality events; Automatic classification; Parseval´s theorem; S-transform; power quality monitoring;
  • fLanguage
    English
  • Journal_Title
    Power Delivery, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8977
  • Type

    jour

  • DOI
    10.1109/TPWRD.2008.923998
  • Filename
    4534395