• DocumentCode
    1167031
  • Title

    Effectiveness of artificial neural networks for first swing stability determination of practical systems

  • Author

    Hobson, E. ; Allen, G.N.

  • Author_Institution
    Univ. South Australia, The Levels, SA, Australia
  • Volume
    9
  • Issue
    2
  • fYear
    1994
  • fDate
    5/1/1994 12:00:00 AM
  • Firstpage
    1062
  • Lastpage
    1068
  • Abstract
    The paper presents an evaluation of the effectiveness of artificial neural networks for rapid determination of critical clearing times for practical networks with varying line outages and load patterns. Studies are reported on the performance of artificial neural networks which have been trained using previously proposed and new training items. It is concluded that artificial neural networks have difficulty in returning consistently accurate answers under varying network conditions
  • Keywords
    electrical faults; learning (artificial intelligence); load (electric); neural nets; power system computer control; power system stability; artificial neural networks; critical clearing times; first swing stability determination; line outages; load patterns; performance; power system control; training; Artificial neural networks; Boilers; Power engineering and energy; Power system dynamics; Power system harmonics; Power system modeling; Power system protection; Power system security; Power system stability; Systems engineering and theory;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/59.317625
  • Filename
    317625