IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i4p1871-d1067808.html
   My bibliography  Save this article

Traveling Wave-Based Fault Localization in FACTS-Compensated Transmission Line via Signal Decomposition Techniques

Author

Listed:
  • Saswati Mishra

    (Department of Electrical Engineering, National Institute of Technology Raipur, G. E. Road, Raipur 492010, CG, India)

  • Shubhrata Gupta

    (Department of Electrical Engineering, National Institute of Technology Raipur, G. E. Road, Raipur 492010, CG, India)

  • Anamika Yadav

    (Department of Electrical Engineering, National Institute of Technology Raipur, G. E. Road, Raipur 492010, CG, India)

  • Almoataz Y. Abdelaziz

    (Faculty of Engineering & Technology, Future University in Egypt, Cairo 11835, Egypt)

Abstract

Modern power systems are structurally complex and are vulnerable to undesirable events like faults. In the event of faults in transmission line, accurate fault location improves restoration process, thereby enhancing the reliability of the overall system. Fault location methods (FLMs) are tools which assist in identifying fault locations quickly. However, the accuracy of these FLMs gets affected in the presence of flexible alternating current transmission system (FACTS) devices. Therefore, in this work, the performance of four different signal decomposition techniques aided traveling wave aided FLMs are qualitatively compared in the context of fault localization in FACTS-compensated systems. FLMs based on intrinsic time decomposition (ITD), empirical mode decomposition (EMD), S-transform (ST), and estimation of signal parameters via rotational invariance technique (ESPRIT) are investigated. The accuracy of FLMs is tested for different cases of series, shunt, and series-shunt FACTS-compensated systems. A 500 kV system employed with 100 MVAr FACTS device is used for simulation. The instant of arrival wave at end of transmission line is from all aforementioned FLMs. The obtained ATWs are used in fault localization. Further, the associated percentage errors are calculated. The results suggest that EMD and ESPRIT-based FLMs are more accurate than others.

Suggested Citation

  • Saswati Mishra & Shubhrata Gupta & Anamika Yadav & Almoataz Y. Abdelaziz, 2023. "Traveling Wave-Based Fault Localization in FACTS-Compensated Transmission Line via Signal Decomposition Techniques," Energies, MDPI, vol. 16(4), pages 1-18, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1871-:d:1067808
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/4/1871/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/4/1871/
    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:4:p:1871-:d:1067808. 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.