• DocumentCode
    3147268
  • Title

    Approximations of power system dynamic load characteristics by artificial neural networks

  • Author

    Thomas, Robert J. ; Ku, Bih-Yuan

  • Author_Institution
    Sch. of Electr. Eng., Cornell Univ., Ithaca, NY, USA
  • fYear
    1991
  • fDate
    23-26 Jul 1991
  • Firstpage
    178
  • Lastpage
    182
  • Abstract
    The static and dynamic characteristics of power system loads are critical to obtaining quality operating point predictions or stability calculations. The composite behavior of components at load buses are usually too complicated to be expressed in a simple form. Based on the approximation capability of artificial neural networks the authors explore the possibility of using neural networks to emulate load behaviours. The results verify the potential of load representation by neural networks
  • Keywords
    load (electric); neural nets; power system analysis computing; artificial neural networks; load buses; power system dynamic load characteristics; quality operating point predictions; stability calculations; Artificial neural networks; Frequency; Impedance; Load modeling; Neural networks; Power system dynamics; Power system modeling; Power system planning; Power system stability; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks to Power Systems, 1991., Proceedings of the First International Forum on Applications of
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7803-0065-3
  • Type

    conf

  • DOI
    10.1109/ANN.1991.213482
  • Filename
    213482