• DocumentCode
    1897934
  • Title

    On-line transient stability assessment using artificial neural network

  • Author

    Sawhney, Harinder ; Jeyasurya, B.

  • Author_Institution
    Fac. of Eng. & Appl. Sci., Memorial Univ. of Newfoundland, St. John´´s, Nfld., Canada
  • fYear
    2004
  • fDate
    28-30 July 2004
  • Firstpage
    76
  • Lastpage
    80
  • Abstract
    This paper proposes an application of artificial neural network (ANN) for contingency screening and ranking of a power system with respect to transient stability. Feature selection techniques are used to select the important features as input to the neural network. The proposed scheme is applied to two sample power systems. Results presented show the merit of the scheme for on-line transient stability assessment (TSA).
  • Keywords
    neural nets; online operation; power engineering computing; power system transient stability; artificial neural network; feature selection techniques; online transient stability assessment; Artificial neural networks; Neural networks; Power system dynamics; Power system faults; Power system modeling; Power system reliability; Power system security; Power system stability; Power system transients; Stability criteria;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering, 2004. LESCOPE-04. 2004 Large Engineering systems Conference on
  • Print_ISBN
    0-7803-8386-9
  • Type

    conf

  • DOI
    10.1109/LESCPE.2004.1356272
  • Filename
    1356272