• DocumentCode
    3483777
  • Title

    Artificial neural network approach in determining voltage stability in power system networks

  • Author

    Arunagiri, A. ; Venkatesh, B. ; Morris, Stella

  • Author_Institution
    Fac. of Eng., Multimedia Univ., Cyberjaya, Malaysia
  • Volume
    5
  • fYear
    2002
  • fDate
    18-22 Nov. 2002
  • Firstpage
    2304
  • Abstract
    Voltage stability problems have been one of the major concerns for electric utilities as a result of system heavy loading. As electric power systems are operated under increasingly stressed conditions, the ability to maintain voltage stability becomes a growing concern. This paper reports on an investigation on the application of artificial neural networks (ANNs) in voltage stability assessment. A multilayer feedforward ANN with error back propagation learning is proposed for calculation of voltage stability index (L). Extensive testing of the proposed ANN based approach indicates its viability for power system voltage assessment. Test results are presented on two sample power systems.
  • Keywords
    backpropagation; feedforward neural nets; multilayer perceptrons; power system analysis computing; power system stability; artificial neural network approach; electric utilities; error back propagation learning; multilayer feedforward ANN; power system networks; power system voltage assessment; voltage stability; voltage stability index; Artificial neural networks; Equations; Intelligent networks; Load flow; Neurons; Power system stability; Power systems; System testing; Virtual colonoscopy; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
  • Print_ISBN
    981-04-7524-1
  • Type

    conf

  • DOI
    10.1109/ICONIP.2002.1201904
  • Filename
    1201904