• DocumentCode
    2672574
  • Title

    Adaptive Strategies in Power Systems Protection Using Artificial Intelligence Techniques

  • Author

    Bittencourt, A.A. ; de Carvalho, M.R. ; Rolim, J.G.

  • Author_Institution
    Dept. of Electr. Eng., Fed. Univ. of Santa Catarina, Florianopolis, Brazil
  • fYear
    2009
  • fDate
    8-12 Nov. 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The present generation of digital protection devices allows the implementation of adaptive strategies for power system protection. This paper presents an overview of the use of artificial intelligence (AI) techniques to improve some aspects of power systems protection, especially adaptive protection. Each technique is briefly described and in the sequence some applications of this technique to the problem being discussed are presented. The study focuses on the following techniques: multi-agent systems, artificial neural networks, genetic algorithms, expert systems and fuzzy logic. This review shows that with the technology available today, some old unsolved issues of power system protection can now be solved and well-known protection philosophies can become more effective and reliable.
  • Keywords
    artificial intelligence; expert systems; fuzzy logic; genetic algorithms; multi-agent systems; neural nets; power engineering computing; power system protection; artificial intelligence techniques; artificial neural networks; digital protection devices; expert systems; fuzzy logic; genetic algorithms; multiagent systems; power systems protection; Adaptive systems; Artificial intelligence; Artificial neural networks; Expert systems; Fuzzy logic; Genetic algorithms; Multiagent systems; Power generation; Power system protection; Power system reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent System Applications to Power Systems, 2009. ISAP '09. 15th International Conference on
  • Conference_Location
    Curitiba
  • Print_ISBN
    978-1-4244-5097-8
  • Electronic_ISBN
    978-1-4244-5098-5
  • Type

    conf

  • DOI
    10.1109/ISAP.2009.5352943
  • Filename
    5352943