• DocumentCode
    1578421
  • Title

    Detection of downed conductor in distribution system

  • Author

    Yang, Ming-Ta ; Gu, Jhy-Cherng ; Guan, Jin-Lung

  • Author_Institution
    Dept. of Electr. Eng., St. John´´s & St. Mary´´s Inst. of Technol., Tamsui, Taiwan
  • fYear
    2005
  • Firstpage
    1107
  • Abstract
    The aim of this paper is to present an analysis and simulation methodology to enhance the detection robustness of high impedance fault (HIF) in the distribution feeder. The techniques of discrete wavelet transformations (DWT) and neural networks (NN) have been widely applied in power system research. Consequently, this study developed a novel technique to effectively discriminate between the HIF and the switch operations by combining DWT with NN. The simulated results clearly show that the proposed technique can accurately identify the HIF.
  • Keywords
    conductors (electric); discrete wavelet transforms; neural nets; power distribution faults; power engineering computing; discrete wavelet transformations; distribution system; downed conductor detection; high impedance fault; neural networks; Analytical models; Conductors; Discrete wavelet transforms; Electrical fault detection; Fault detection; Impedance; Neural networks; Power system simulation; Robustness; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society General Meeting, 2005. IEEE
  • Print_ISBN
    0-7803-9157-8
  • Type

    conf

  • DOI
    10.1109/PES.2005.1489429
  • Filename
    1489429