IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/8929066.html
   My bibliography  Save this article

Distribution Network Disaster Early Warning and Production Decision Support System Based on Multisource Data

Author

Listed:
  • Shan Li
  • Bin Feng
  • Wei Zhang
  • Yubin Feng
  • Zhidu Huang
  • Naeem Jan

Abstract

Aiming at the problems of long warning time and low warning accuracy in the traditional distribution network disaster early warning and production decision support systems, a distribution network disaster early warning and production decision support system based on multisource data is designed. The forecast information is collected through the data collector, the wind load and lightning trip rate of the line are calculated, all of the information is integrated together for multisource data fusion processing, and the distribution network disaster early warning model is constructed in accordance with the system hardware, which is designed with a data collector, gateway, man-machine interface, fault analysis module, disaster early warning module, and expert decision support module. According to the system hardware and software design, the design of a distribution network disaster early warning and production decision support system based on multisource data is realized. The simulation results show that the system has high accuracy and a short warning time.

Suggested Citation

  • Shan Li & Bin Feng & Wei Zhang & Yubin Feng & Zhidu Huang & Naeem Jan, 2023. "Distribution Network Disaster Early Warning and Production Decision Support System Based on Multisource Data," Mathematical Problems in Engineering, Hindawi, vol. 2023, pages 1-10, May.
    • Handle: RePEc:hin:jnlmpe:8929066
    DOI: 10.1155/2023/8929066
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/2023/8929066.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/mpe/2023/8929066.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2023/8929066?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:hin:jnlmpe:8929066. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.