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Traveling Wave Energy Analysis of Faults on Power Distribution Systems

Author

Listed:
  • Miguel Jiménez-Aparicio

    (Sandia National Laboratories, Albuquerque, NM 87123, USA)

  • Matthew J. Reno

    (Sandia National Laboratories, Albuquerque, NM 87123, USA)

  • Felipe Wilches-Bernal

    (Sandia National Laboratories, Albuquerque, NM 87123, USA)

Abstract

This paper explores the most important factors that define the Traveling Wave (TW) propagation on distribution systems. The factors considered in this work are: the distance to the fault location, the fault type, and the crossing of system elements (such as regulators, capacitor banks, laterals, and extra loads within the protection zones). This work uses a realistic, yet simplified, distribution system composed of two protection zones, in which, several combinations of the previously mentioned factors are considered. The simulated fault measurements undergo a signal processing stage in which, first, they are decomposed into independent modes using the Karrenbauer transform. Second, a time–frequency representation is obtained using the Stationary Wavelet Transform (SWT), dividing the signal into several frequency bands. Finally, the Parseval’s Energy (PE) theorem is applied to calculate the signal energy in each frequency band. A qualitative analysis is performed based on the previously calculated energies to outline which are the factors that most affect the TW energy during propagation. The results show that distance, the presence of regulators, either in the propagation path or upstream, and the type of fault are the main factors that affect TW propagation across the system, and therefore they should be considered for TW-based protection schemes for distribution systems.

Suggested Citation

  • Miguel Jiménez-Aparicio & Matthew J. Reno & Felipe Wilches-Bernal, 2022. "Traveling Wave Energy Analysis of Faults on Power Distribution Systems," Energies, MDPI, vol. 15(8), pages 1-28, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:8:p:2741-:d:789913
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    References listed on IDEAS

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    1. Gururajapathy, S.S. & Mokhlis, H. & Illias, H.A., 2017. "Fault location and detection techniques in power distribution systems with distributed generation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 949-958.
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    Cited by:

    1. Miguel Jiménez-Aparicio & Javier Hernández-Alvidrez & Armando Y. Montoya & Matthew J. Reno, 2022. "Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks," Energies, MDPI, vol. 15(20), pages 1-22, October.

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