IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i8p2741-d789913.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/8/2741/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/8/2741/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Saeid Khavari & Rahman Dashti & Hamid Reza Shaker & Athila Santos, 2020. "High Impedance Fault Detection and Location in Combined Overhead Line and Underground Cable Distribution Networks Equipped with Data Loggers," Energies, MDPI, vol. 13(9), pages 1-15, May.
    2. Hernandez-Matheus, Alejandro & Löschenbrand, Markus & Berg, Kjersti & Fuchs, Ida & Aragüés-Peñalba, Mònica & Bullich-Massagué, Eduard & Sumper, Andreas, 2022. "A systematic review of machine learning techniques related to local energy communities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    3. Jia, Ke & Gu, Chenjie & Li, Lun & Xuan, Zhengwen & Bi, Tianshu & Thomas, David, 2018. "Sparse voltage amplitude measurement based fault location in large-scale photovoltaic power plants," Applied Energy, Elsevier, vol. 211(C), pages 568-581.
    4. Saidatul Habsah Asman & Nur Fadilah Ab Aziz & Ungku Anisa Ungku Amirulddin & Mohd Zainal Abidin Ab Kadir, 2021. "Transient Fault Detection and Location in Power Distribution Network: A Review of Current Practices and Challenges in Malaysia," Energies, MDPI, vol. 14(11), pages 1-37, May.
    5. Jun Yin Lee & Renuga Verayiah & Kam Hoe Ong & Agileswari K. Ramasamy & Marayati Binti Marsadek, 2020. "Distributed Generation: A Review on Current Energy Status, Grid-Interconnected PQ Issues, and Implementation Constraints of DG in Malaysia," Energies, MDPI, vol. 13(24), pages 1-40, December.
    6. Sellak, Hamza & Ouhbi, Brahim & Frikh, Bouchra & Palomares, Iván, 2017. "Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1544-1577.
    7. Moamin A. Mahmoud & Naziffa Raha Md Nasir & Mathuri Gurunathan & Preveena Raj & Salama A. Mostafa, 2021. "The Current State of the Art in Research on Predictive Maintenance in Smart Grid Distribution Network: Fault’s Types, Causes, and Prediction Methods—A Systematic Review," Energies, MDPI, vol. 14(16), pages 1-27, August.
    8. Pascal Hategekimana & Adria Junyent Ferre & Joan Marc Rodriguez Bernuz & Etienne Ntagwirumugara, 2022. "Fault Detecting and Isolating Schemes in a Low-Voltage DC Microgrid Network from a Remote Village," Energies, MDPI, vol. 15(12), pages 1-16, June.
    9. Zhidi Lin & Dongliang Duan & Qi Yang & Xuemin Hong & Xiang Cheng & Liuqing Yang & Shuguang Cui, 2020. "Data-Driven Fault Localization in Distribution Systems with Distributed Energy Resources," Energies, MDPI, vol. 13(1), pages 1-16, January.
    10. Masoud Ahmadipour & Hashim Hizam & Mohammad Lutfi Othman & Mohd Amran Mohd Radzi & Nikta Chireh, 2019. "A Fast Fault Identification in a Grid-Connected Photovoltaic System Using Wavelet Multi-Resolution Singular Spectrum Entropy and Support Vector Machine," Energies, MDPI, vol. 12(13), pages 1-18, June.
    11. Jinrui Tang & Binyu Xiong & Chen Yang & Cuilan Tang & Yang Li & Guoxing Su & Xinhao Bian, 2019. "Development of an Integrated Power Distribution System Laboratory Platform Using Modular Miniature Physical Elements: A Case Study of Fault Location," Energies, MDPI, vol. 12(19), pages 1-19, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:8:p:2741-:d:789913. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.