• DocumentCode
    3105903
  • Title

    Identification of aged cable section in 12.5 kV URD system based on Frequency Spectrum

  • Author

    Pushpanathan, B. ; Grzybowski, S. ; Bialek, T.O.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Mississippi State Univ., Starkville, MS, USA
  • fYear
    2012
  • fDate
    7-10 May 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Underground residential distribution (URD) power cables are aged due to electrical, thermal, mechanical and environmental stress during their service. For utilities, the recent dielectric conditions of the cables are of much interest. Fast Fourier Transform Analysis of the impulse wave propagating in URD is one of the online non-destructive methods to estimate the cable insulation condition. In this study, the radial URD system with aged cable sections was modeled using EMTP for transient studies. A switching transient was simulated in the energized model of the URD system. Based on the Frequency Spectrum of the voltages at different points in the model URD, an aged cable section identification methodology using feature classification is presented in this paper.
  • Keywords
    EMTP; dielectric materials; fast Fourier transforms; feature extraction; pattern classification; power cable insulation; switching transients; underground residential distribution systems; EMTP; aged cable section identification; cable insulation condition; cable section identification methodology; cables dielectric conditions; electrical stress; environmental stress; fast Fourier transform analysis; feature classification; frequency spectrum; frequency spectrum-based URD system; impulse wave propagation; mechanical stress; online nondestructive methods; radial URD system; switching transient; thermal stress; underground residential distribution power cables; voltage 12.5 kV; Aging; Neural networks; Power cable insulation; Power cables; Transient analysis; Aged cable identification; Aged cable model; EMTP Simulation; Fast Fourier Transform; Frequency spectrum feature extraction; Heuristic Original Probabilistic Neural Network; On-line cable condition assessment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Transmission and Distribution Conference and Exposition (T&D), 2012 IEEE PES
  • Conference_Location
    Orlando, FL
  • ISSN
    2160-8555
  • Print_ISBN
    978-1-4673-1934-8
  • Electronic_ISBN
    2160-8555
  • Type

    conf

  • DOI
    10.1109/TDC.2012.6281656
  • Filename
    6281656