• DocumentCode
    2440968
  • Title

    Application of neural networks to power system security: technology and trends

  • Author

    Fischl, R.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USA
  • Volume
    6
  • fYear
    1994
  • fDate
    27 Jun- 2 Jul 1994
  • Firstpage
    3719
  • Abstract
    This paper presents an overview of the application of artificial neural networks (NN) to power system security assessment. It is noted that although the majority of NN architectures used is the multilayered perceptron, some work has been done to use the Hopfield and the Kohonen networks. In either case, the present applications are illustrated using small power systems, and the key issues are the selection of the input data, training set and the evaluation of the NN design in terms of its accuracy in predicting the security of the power system. Most of the discussion in this paper is concerned with the latter issue since it has not been addressed extensively in the literature
  • Keywords
    neural nets; power system analysis computing; power system security; Hopfield neural net; Kohonen neural networks; input data; multilayered perceptron; neural networks; power system security assessment; training set; Application software; Artificial neural networks; Computer networks; Data security; Neural networks; Neurons; Performance analysis; Power system analysis computing; Power system security; Power systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-1901-X
  • Type

    conf

  • DOI
    10.1109/ICNN.1994.374801
  • Filename
    374801