• DocumentCode
    3246201
  • Title

    MOSELM approach for Voltage Stability Indicator using phasor measurement units

  • Author

    Abidin, I.Z. ; Keem Siah Yap ; Saadun, Nira ; Abdullah, Sheikh Kamar Sheikh ; Mohd Sarmin, M.K.N.

  • Author_Institution
    Univ. Tenaga Nasional (UNITEN), Kajang, Malaysia
  • fYear
    2012
  • fDate
    2-5 Dec. 2012
  • Firstpage
    510
  • Lastpage
    514
  • Abstract
    Voltage stability assessment is important in order to ensure a stable power system. Two algorithms were discussed in this paper which looks into estimating voltage stability based upon Thevenin Equivalent values in a system using Voltage and Current Phasors for different loading values. The first algorithm uses a Kalman filter based formulation. The second method uses an Online Learning approach known as the Modified Online Sequence Extreme Learning Machine (MOSELM). Results show that the Kalman Filter approach is capable of analyzing voltage stability but it requires some user specified information for tuning. On the other hand, the MOSELM approach show that it is capable of producing the same result as the Kalman Filter approach but require less amount of user specified information.
  • Keywords
    Kalman filters; learning (artificial intelligence); phasor measurement; power engineering computing; power system stability; Kalman filter; MOSELM approach; Thevenin equivalent values; current phasors; modified online sequence extreme learning machine; online learning approach; phasor measurement units; power system; voltage phasors; voltage stability assessment; voltage stability indicator; Kalman filters; Learning systems; Power system stability; Reactive power; Stability analysis; Voltage measurement; Artificial Intelligence; Kalman Filter; Online Sequential Extreme Learning Machine; Phasor Measurement Units; Voltage Stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy (PECon), 2012 IEEE International Conference on
  • Conference_Location
    Kota Kinabalu
  • Print_ISBN
    978-1-4673-5017-4
  • Type

    conf

  • DOI
    10.1109/PECon.2012.6450267
  • Filename
    6450267