• DocumentCode
    3305130
  • Title

    Power system equivalent based on an artificial neural network

  • Author

    Pavic, Ivica ; Hebel, Zdravko ; Delimar, Marko

  • Author_Institution
    Dept. of Power Syst., Zagreb Univ., Croatia
  • fYear
    2001
  • fDate
    19-22 June 2001
  • Firstpage
    359
  • Abstract
    Very often, insufficient data is exchanged between neighboring power systems for quality load flow and contingency analysis. The external systems, therefore, have to be substituted with the power system equivalents. In this paper the possibilities of using an artificial neural network as the external power system equivalent is explored, to be used for load flow and contingency analysis within the internal power system. The experiment is performed on a standard IEEE 24-node network which is, for the purposes of testing, divided into two systems (the internal and the external) and the external system is modeled by a neural network. The results are presented and discussed.
  • Keywords
    load management; neural nets; power system simulation; IEEE 24-node network; artificial neural network; contingency analysis; experiment; external power system equivalent; load flow analysis; power system modeling; Artificial neural networks; Load flow; Load flow analysis; Neural networks; Power system analysis computing; Power system interconnection; Power system modeling; Power system reliability; Power systems; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology Interfaces, 2001. ITI 2001. Proceedings of the 23rd International Conference on
  • ISSN
    1330-1012
  • Print_ISBN
    953-96769-3-2
  • Type

    conf

  • DOI
    10.1109/ITI.2001.938042
  • Filename
    938042