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Towards the Text Compression Based Feature Extraction in High Impedance Fault Detection

Author

Listed:
  • Tomáš Vantuch

    (Centre ENET at VŠB—Technical University of Ostrava, 17. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic)

  • Michal Prílepok

    (Centre ENET at VŠB—Technical University of Ostrava, 17. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic)

  • Jan Fulneček

    (Centre ENET at VŠB—Technical University of Ostrava, 17. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic)

  • Roman Hrbáč

    (Centre ENET at VŠB—Technical University of Ostrava, 17. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic)

  • Stanislav Mišák

    (Centre ENET at VŠB—Technical University of Ostrava, 17. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic)

Abstract

High impedance faults of medium voltage overhead lines with covered conductors can be identified by the presence of partial discharges. Despite it is a subject of research for more than 60 years, online partial discharges detection is always a challenge, especially in environment with heavy background noise. In this paper, a new approach for partial discharge pattern recognition is presented. All results were obtained on data, acquired from real 22 kV medium voltage overhead power line with covered conductors. The proposed method is based on a text compression algorithm and it serves as a signal similarity estimation, applied for the first time on partial discharge pattern. Its relevancy is examined by three different variations of classification model. The improvement gained on an already deployed model proves its quality.

Suggested Citation

  • Tomáš Vantuch & Michal Prílepok & Jan Fulneček & Roman Hrbáč & Stanislav Mišák, 2019. "Towards the Text Compression Based Feature Extraction in High Impedance Fault Detection," Energies, MDPI, vol. 12(11), pages 1-13, June.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:11:p:2148-:d:237325
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    References listed on IDEAS

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    1. A. Prinzie & D. Van Den Poel, 2007. "Random Forrests for Multiclass classification: Random Multinomial Logit," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/435, Ghent University, Faculty of Economics and Business Administration.
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    Cited by:

    1. Francinei L. Vieira & Pedro H. M. Santos & José M. Carvalho Filho & Roberto C. Leborgne & Marino P. Leite, 2019. "A Voltage-Based Approach for Series High Impedance Fault Detection and Location in Distribution Systems Using Smart Meters," Energies, MDPI, vol. 12(15), pages 1-16, August.

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