IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i23p7914-d1293927.html
   My bibliography  Save this article

Fault Detection on Power Transmission Line Based on Wavelet Transform and Scalogram Image Analysis

Author

Listed:
  • Ahmed Sabri Altaie

    (Department of System Engineering and Automation, University Carlos III of Madrid, Avada de la Universidad 30, 28911 Leganes, Madrid, Spain)

  • Ammar Abbas Majeed

    (Department of System Engineering and Automation, University Carlos III of Madrid, Avada de la Universidad 30, 28911 Leganes, Madrid, Spain)

  • Mohamed Abderrahim

    (Department of System Engineering and Automation, University Carlos III of Madrid, Avada de la Universidad 30, 28911 Leganes, Madrid, Spain)

  • Afaneen Alkhazraji

    (Communication Engineering Department, University of Technology-Iraq, Al-Sina’a St., Baghdad 10066, Iraq)

Abstract

Given the massive increase in demand for electrical energy, particularly owing to global climate change and population expansion, as well as the development of complicated electrical systems due to the urgent need for a sophisticated component to enhance power delivery, it becomes important to adopt a smart and contemporary approach that is also appropriate for the aim of protecting transmission lines (TLs) and ensuring the continuous delivery of electric power to customers. Consequently, a unique and highly reliable approach for identifying faults in TLs is presented in this work, which employs Wavelet Transform and is evaluated using Matlab simulation. Wavelets of various kinds were utilized to demonstrate their dependability. Furthermore, utilizing this approach has shown itself to be highly successful and has yielded spectacular results even when it is used on a complicated electrical network. Moreover, many types of faults were presented and afterward evaluated and verified for the network in various settings, which also demonstrated their potential to recognize faults within a relatively short space of time. This innovation will alter the idea of fault detection by providing a complete and integrated model for detecting faults in a TL, and it may be regarded as a revolution in the renewal of core principles in TL protection.

Suggested Citation

  • Ahmed Sabri Altaie & Ammar Abbas Majeed & Mohamed Abderrahim & Afaneen Alkhazraji, 2023. "Fault Detection on Power Transmission Line Based on Wavelet Transform and Scalogram Image Analysis," Energies, MDPI, vol. 16(23), pages 1-19, December.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:23:p:7914-:d:1293927
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/23/7914/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/23/7914/
    Download Restriction: no
    ---><---

    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:16:y:2023:i:23:p:7914-:d:1293927. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.