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A Voltage-Based Approach for Series High Impedance Fault Detection and Location in Distribution Systems Using Smart Meters

Author

Listed:
  • Francinei L. Vieira

    (Instituto de Sistemas Elétricos e Energia, Universidade Federal de Itajubá, Av. BPS 1303, Itajubá 37500-903, Brazil)

  • Pedro H. M. Santos

    (Instituto de Sistemas Elétricos e Energia, Universidade Federal de Itajubá, Av. BPS 1303, Itajubá 37500-903, Brazil)

  • José M. Carvalho Filho

    (Instituto de Sistemas Elétricos e Energia, Universidade Federal de Itajubá, Av. BPS 1303, Itajubá 37500-903, Brazil)

  • Roberto C. Leborgne

    (Universidade Federal do Rio Grande do Sul, Av. Osvaldo Aranha 99, Porto Alegre 90035-190, Brazil)

  • Marino P. Leite

    (Instituto de Sistemas Elétricos e Energia, Universidade Federal de Itajubá, Av. BPS 1303, Itajubá 37500-903, Brazil)

Abstract

High impedance faults (HIFs) have been a major concern for protecting distribution systems and public safety hazards when involving downed conductors. The deployment of smarter grids brings new technologies for smart monitoring, automation, and protection of distribution networks. This paper presents a new method for a series of HIF detection and location in primary distribution feeders, using voltage unbalance measurements collected from smart meters (SMs) installed at low-voltage end-users. The methodology was tested in MATLAB and Simulink through steady-state simulations of a typical 13.8 kV distribution system, under load unbalance and different fault scenarios. Results show that the proposed method is robust and accurate for the detection of blown fuses and broken conductors, with or without ground faults, located either at the source or the load-side. The ease of implementation in SM design, formulation of parameters, and reliable simulation results show potential real-life applications.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:15:p:3022-:d:255117
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    References listed on IDEAS

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    1. 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.
    2. Mishari Metab Almalki & Constantine J. Hatziadoniu, 2018. "Classification of Many Abnormal Events in Radial Distribution Feeders Using the Complex Morlet Wavelet and Decision Trees," Energies, MDPI, vol. 11(3), pages 1-16, March.
    3. Veerapandiyan Veerasamy & Noor Izzri Abdul Wahab & Rajeswari Ramachandran & Muhammad Mansoor & Mariammal Thirumeni & Mohammad Lutfi Othman, 2018. "High Impedance Fault Detection in Medium Voltage Distribution Network Using Discrete Wavelet Transform and Adaptive Neuro-Fuzzy Inference System," Energies, MDPI, vol. 11(12), pages 1-24, November.
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    Cited by:

    1. Ednardo Rocha & Max Pimentel Filho & Melinda Cruz & Marcos Almeida & Manoel Medeiros Júnior, 2020. "A New Linear State Estimator for Fault Location in Distribution Systems Based on Backward-Forward Currents Sweep," Energies, MDPI, vol. 13(11), pages 1-23, May.
    2. Krzysztof Lowczowski & Jozef Lorenc & Jozef Zawodniak & Grzegorz Dombek, 2020. "Detection and Location of Earth Fault in MV Feeders Using Screen Earthing Current Measurements," Energies, MDPI, vol. 13(5), pages 1-24, March.
    3. Piotr Hoduń & Michał Borecki, 2021. "Reliability Assessment of MV Power Connections," Energies, MDPI, vol. 14(21), pages 1-15, October.

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