• DocumentCode
    3091174
  • Title

    A fault locator for transmission lines based on Prony method

  • Author

    Tawfik, M.M. ; Morcos, M.M.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Kansas State Univ., Manhattan, KS, USA
  • Volume
    2
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    943
  • Abstract
    The Prony method is a new tool in the area of power system protection. In this work it is used to locate faults on long lines. The estimation is based on the transients generated by traveling waves initiated by the fault. The proposed scheme comprises a Prony-based signal processor and an ANN-based inference system. Input data is generated using the Alternative Transient Program (ATP). A three-phase, frequency-dependent (FD) transmission line model was used. Two schemes are tested. The first scheme is set using the Prony residues´ calculations. The second scheme utilizes Prony full calculations. The second scheme is tested using the data employed in the ANN training and new data sets. The proposed locator has a good level of accuracy
  • Keywords
    backpropagation; fault location; neural nets; power system analysis computing; power transmission faults; power transmission lines; power transmission protection; transmission line theory; ANN training; ANN-based inference system; Alternative Transient Program; Prony method; Prony-based signal processor; backpropagation; fault locator; frequency-dependent transmission line model; long transmission lines; power system protection; three-phase; Artificial neural networks; Fault location; Impedance; Power system modeling; Power system transients; Power transmission lines; Protection; Signal processing algorithms; Transmission line theory; Transmission lines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society Summer Meeting, 1999. IEEE
  • Conference_Location
    Edmonton, Alta.
  • Print_ISBN
    0-7803-5569-5
  • Type

    conf

  • DOI
    10.1109/PESS.1999.787443
  • Filename
    787443