IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i9p1770-d229847.html
   My bibliography  Save this article

An Analytic Method for Power System Fault Diagnosis Employing Topology Description

Author

Listed:
  • Biao Xu

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Xianggen Yin

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Dali Wu

    (Wuhan Second Ship Design and Research Institute, Wuhan 430064, China)

  • Shuai Pang

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yikai Wang

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

When a fault occurs in a power system, fault section estimation is the primary premise for troubleshooting and power recovery, and an effective fault diagnosis system will play a big role in decision making. However, the topology information is not well employed in existing fault diagnosis methods, and it is complex and time consuming to analyze the relationship between the protective devices and the sections. In this paper, a novel analytic method which employs topology description is proposed for fault diagnosis. The topology descriptions of the sections and the protective devices are firstly established according to the network structure, and based on which the operating logic and the cooperative relationship of the protective devices can be easily analyzed by matrix operation. Considering the factors of logic error and communication error, the fault diagnosis problem is formulated as an integer programming problem and can be solved by intelligent algorithm. The case studies of different power systems show that the proposed method can quickly identify the fault section, even with the abnormal operation or error alarm of protective devices.

Suggested Citation

  • Biao Xu & Xianggen Yin & Dali Wu & Shuai Pang & Yikai Wang, 2019. "An Analytic Method for Power System Fault Diagnosis Employing Topology Description," Energies, MDPI, vol. 12(9), pages 1-17, May.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:9:p:1770-:d:229847
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/9/1770/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/12/9/1770/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Ziyu Bai & Guoqiang Sun & Haixiang Zang & Ming Zhang & Peifeng Shen & Yi Liu & Zhinong Wei, 2019. "Identification Technology of Grid Monitoring Alarm Event Based on Natural Language Processing and Deep Learning in China," Energies, MDPI, vol. 12(17), pages 1-19, August.

    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:12:y:2019:i:9:p:1770-:d:229847. 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.