• DocumentCode
    2500145
  • Title

    Small signal stability assessment and control of power systems

  • Author

    Mirfendereski, S. ; Wahab, Noor Izzri Abdul ; Jasni, J. ; Othman, M.L.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Univ. Putra Malaysia, Serdang, Malaysia
  • fYear
    2012
  • fDate
    6-7 June 2012
  • Firstpage
    515
  • Lastpage
    520
  • Abstract
    A method for assessment and control of small signal stability (SSS) has been proposed in this paper. As the angle of rotor represents the stability of the system, the proposed method tries to assess the instability and its solutions by using comparison instead of time consuming conventional method. The idea divides power networks into different areas. The system has sub-controllers and main controller with different authorities which will results in fast and reliable prediction and control of SSS. Artificial intelligence could be used as a tool that would give the ability of learning to the system which gives the system the opportunity to response fast and accurate in future problems.
  • Keywords
    learning (artificial intelligence); power engineering computing; power system control; power system stability; SSS prediction reliability; artificial intelligence; power system control; rotor angle; small-signal stability assessment; system stability; Control systems; Eigenvalues and eigenfunctions; Equations; Power system dynamics; Power system stability; Stability criteria; Artificial Intelligence; Assessment of Instability preventive control; Rescheduling; Small Signal Stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering and Optimization Conference (PEDCO) Melaka, Malaysia, 2012 Ieee International
  • Conference_Location
    Melaka
  • Print_ISBN
    978-1-4673-0660-7
  • Type

    conf

  • DOI
    10.1109/PEOCO.2012.6230920
  • Filename
    6230920