• DocumentCode
    3410257
  • Title

    Dynamic compensator design for HV AC power system using artificial neural networks

  • Author

    Salim, G.A. ; Choudhry, M.A. ; Ellithy, K.A.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., West Virginia Univ., Morgantown, WV, USA
  • fYear
    1996
  • fDate
    31 Mar-2 Apr 1996
  • Firstpage
    202
  • Lastpage
    205
  • Abstract
    This paper presents a method for designing a dynamic compensator based on artificial neural networks (ANN). The ANN is trained to give the proper compensator parameters (X, Tz) so as to always assign certain eigenvalues to desired locations in the output feedback system. The eigenvalues of concern are those associated with the angle δ and speed ω. These eigenvalues are to be assigned to the specified locations under variations in several system parameters [static nonlinear load parameters Ap and Aq, transmission line reactance, xe, and generated real power, PG]. The exact and ANN´s results of compensator´s parameters are plotted. In addition speed response is provided for the compensated and uncompensated systems. Results show that the ANN can be used on line once the off line training is performed to determine the compensator data so as to maintain the desired response of the system under variations in system parameters
  • Keywords
    HVDC power transmission; compensation; feedback; neural nets; power system control; static VAr compensators; HV AC power system; artificial neural networks; dynamic compensator design; eigenvalues assignment; output feedback system; uncompensated systems; Artificial neural networks; Closed loop systems; Computer networks; Eigenvalues and eigenfunctions; Open loop systems; Output feedback; Power system dynamics; Power systems; Static VAr compensators; Transfer functions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Theory, 1996., Proceedings of the Twenty-Eighth Southeastern Symposium on
  • Conference_Location
    Baton Rouge, LA
  • ISSN
    0094-2898
  • Print_ISBN
    0-8186-7352-4
  • Type

    conf

  • DOI
    10.1109/SSST.1996.493499
  • Filename
    493499