IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i12p4307-d837151.html
   My bibliography  Save this article

The Identification of Travelling Waves in a Voltage Sensor Signal in a Medium Voltage Grid Using the Short-Time Matrix Pencil Method

Author

Listed:
  • Piotr Łukaszewski

    (Institute of Electrical Power Engineering, Warsaw University of Technology, 75 Koszykowa St., 00-662 Warsaw, Poland)

  • Łukasz Nogal

    (Institute of Electrical Power Engineering, Warsaw University of Technology, 75 Koszykowa St., 00-662 Warsaw, Poland)

  • Artur Łukaszewski

    (Institute of Electrical Power Engineering, Warsaw University of Technology, 75 Koszykowa St., 00-662 Warsaw, Poland)

Abstract

Most of the fault wave localization methods are based on the analysis of line current transformed by current transformers and are limited to high voltage grids. Fault wave localization in medium voltage grids is still being developed. This paper presents a new real-time algorithm for the identification of travelling waves in a distribution grid using voltage signal and the short-time matrix pencil method. To obtain the secondary side voltage waveforms at substation, the model of a resistive voltage sensor based on the broadband measurements from 10 Hz to 20 MHz was developed. The tested sensor amplifies the frequencies associated with travelling waves more than utility frequency allowing for the identification. Short-circuit simulations on the IEEE 34-bus feeder was performed to test the algorithm. The developed method can detect even the waves of low amplitude.

Suggested Citation

  • Piotr Łukaszewski & Łukasz Nogal & Artur Łukaszewski, 2022. "The Identification of Travelling Waves in a Voltage Sensor Signal in a Medium Voltage Grid Using the Short-Time Matrix Pencil Method," Energies, MDPI, vol. 15(12), pages 1-16, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:12:p:4307-:d:837151
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/12/4307/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/12/4307/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Dan Liu & Yiqun Kang & Heng Luo & Xiaotong Ji & Kan Cao & Hengrui Ma, 2023. "A Grid Status Analysis Method with Large-Scale Wind Power Access Using Big Data," Energies, MDPI, vol. 16(12), pages 1-12, June.

    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:12:p:4307-:d:837151. 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.