• DocumentCode
    1948121
  • Title

    Load modelling in commercial power systems using neural networks

  • Author

    Song, Y.H. ; Dang, D.Y.

  • Author_Institution
    Sch. of Electr. Eng. & Electron., Liverpool John Moores Univ., UK
  • fYear
    1994
  • fDate
    1-5 May 1994
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Power system load modelling is of vital importance in power flow, transient stability and voltage stability studies. It is, however, a very difficult task because load representation is qualitatively different in many aspects. Conventional approaches employ mathematical models to represent the steady and dynamic characteristics of various loads. With the advent of neural computing, attempts have constantly been made to address this problem by using this new technique. This paper discusses the applications of neural networks to the representation of the aggregation of busbar loads which are comprised of mixed but known composition
  • Keywords
    busbars; digital simulation; load flow; neural nets; power system analysis computing; power system stability; power system transients; applications; busbar; computer simulation; load modelling; load representation; mathematical models; neural networks; power flow; power systems; transient stability; voltage stability; Industrial power systems; Load flow; Load modeling; Mathematical model; Neural networks; Power system dynamics; Power system modeling; Power system stability; Power system transients; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial and Commercial Power Systems Technical Conference, 1994. Conference Record, Papers Presented at the 1994 Annual Meeting, 1994 IEEE
  • Conference_Location
    Irvine, CA
  • Print_ISBN
    0-7803-1877-3
  • Type

    conf

  • DOI
    10.1109/ICPS.1994.303546
  • Filename
    303546