• DocumentCode
    2326195
  • Title

    Transient identification in composite conductor circuits using fuzzy neural network

  • Author

    Wang, G.S. ; Bo, Z.Q. ; Wang, P.Y.

  • Author_Institution
    Groupe Schneider, UK
  • Volume
    2
  • fYear
    1998
  • fDate
    18-21 Aug 1998
  • Firstpage
    870
  • Abstract
    This paper presents a method for transient identification in composite conductor circuits using fuzzy neural networks (FNN), in which a special designed detector is employed to capture transient signals induced by faults and switching operations, which produces training samples for the fuzzy neural network. A digital modeling is conducted on a typical 400 kV composite conductor circuit, and the test results have proven that the FNN is able to identify a fault or a switching operation under various system and fault conditions
  • Keywords
    fuzzy neural nets; power system faults; power system simulation; power system transients; 400 kV; composite conductor circuits; computer simulation; fault identification; fuzzy neural network; power systems; switching operations; transient identification; transient signals capture; Circuit faults; Circuit testing; Conductors; Detectors; Electrical fault detection; Fault detection; Fault diagnosis; Fuzzy neural networks; Signal design; Switching circuits;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power System Technology, 1998. Proceedings. POWERCON '98. 1998 International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-4754-4
  • Type

    conf

  • DOI
    10.1109/ICPST.1998.729209
  • Filename
    729209