• DocumentCode
    3192385
  • Title

    A New Protection Detection Technique for High Impedance Fault Using Neural Network

  • Author

    Eissa, M.M. ; Sowilam, G.M.A. ; Sharaf, A.M.

  • Author_Institution
    SMIEEE, Department of Electrical Engineering, Faculty of Engineering, Helwan University, EGYPT. mmmeissa@yahoo.com
  • fYear
    2006
  • fDate
    38899
  • Firstpage
    146
  • Lastpage
    151
  • Abstract
    The paper presents the application of Neural Network technique as a pattern recognition to high impedance faults (HIFs). The relay is based on a novel low-frequency (3rd and 5th harmonic feature diagnostic vector). The currents and voltages are used as a featured extracted signals for fault discrimination. The focus of this paper is to design a robust ANN-based relay, which can determine the high impedance low current faults on distribution radial electrical systems. A variety of faults and system conditions have been simulated to evaluate the reliability and sensitivity of the proposed technique.
  • Keywords
    Fault detection; Feature extraction; Impedance; Neural networks; Pattern recognition; Protection; Protective relaying; Relays; Robustness; Voltage; ANN based relaying; EHV Transmission line; Matlab/Simulink; Non linear ARC model; Pattern recognition; Protective Relaying;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering, 2006 Large Engineering Systems Conference on
  • Conference_Location
    Halifax, NS, Canada
  • Print_ISBN
    1-4244-0556-4
  • Electronic_ISBN
    1-4244-0557-2
  • Type

    conf

  • DOI
    10.1109/LESCPE.2006.280378
  • Filename
    4059384