• DocumentCode
    3102767
  • Title

    Application of ensemble Kalman filter in power system state tracking and sensitivity analysis

  • Author

    Li, Yulan ; Huang, Zhenyu ; Zhou, Ning ; Lee, Barry ; Diao, Ruisheng ; Du, Pengwei

  • Author_Institution
    Pacific Northwest Nat. Lab., Richland, WA, USA
  • fYear
    2012
  • fDate
    7-10 May 2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    An ensemble Kalman filter (EnKF) method is proposed to track dynamic states of generators. The algorithm of the EnKF and its application to generator state tracking are presented in detail. The accuracy and sensitivity of the method are analyzed with respect to initial state errors, measurement noise, unknown fault locations, time steps and parameter errors. It is demonstrated through simulation studies that even with some errors in the parameters, the developed EnKF method can still effectively track generator dynamic states.
  • Keywords
    Kalman filters; electric generators; fault location; power grids; power system measurement; sensitivity analysis; tracking; EnKF method; ensemble Kalman filter; generator dynamic states tracking; measurement noise; parameter errors; power system state tracking; sensitivity analysis; state errors; unknown fault locations; Current measurement; Fault location; Generators; Noise; Noise measurement; Power system dynamics; Time measurement; dynamic state tracking; ensemble Kalman filter; power system; sensitivity analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Transmission and Distribution Conference and Exposition (T&D), 2012 IEEE PES
  • Conference_Location
    Orlando, FL
  • ISSN
    2160-8555
  • Print_ISBN
    978-1-4673-1934-8
  • Electronic_ISBN
    2160-8555
  • Type

    conf

  • DOI
    10.1109/TDC.2012.6281499
  • Filename
    6281499