IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v306y2022ipbs0306261921014021.html
   My bibliography  Save this article

Loss reduction strategy and evaluation system based on reasonable line loss interval of transformer area

Author

Listed:
  • Hu, Wei
  • Guo, Qiuting
  • Wang, Wei
  • Wang, Weiheng
  • Song, Shuhong

Abstract

As the wiring of distribution network becomes more and more complex, it is difficult to calculate the theoretical line loss of low-voltage distribution transformer area and the evaluation index of transformer line loss is extensive. In this paper, a reasonable interval calculation model of line loss is established based on the data of electricity information acquisition system. Firstly, the collected data are processed in the image format, and then the line loss calculation model is established based on the convolutional neural network. This model can estimate the reasonable line loss interval according to the operation data of different transformers. On this basis, the line loss evaluation system is established and the loss reduction strategy of abnormal transformer is formed. The method in this paper can be used to evaluate the line loss level of distribution transformer area more accurately. It also can improve the quality and efficiency of line loss lean management and produce certain effect for electric energy conservation and improving economic benefit of power supply.

Suggested Citation

  • Hu, Wei & Guo, Qiuting & Wang, Wei & Wang, Weiheng & Song, Shuhong, 2022. "Loss reduction strategy and evaluation system based on reasonable line loss interval of transformer area," Applied Energy, Elsevier, vol. 306(PB).
    • Handle: RePEc:eee:appene:v:306:y:2022:i:pb:s0306261921014021
    DOI: 10.1016/j.apenergy.2021.118123
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921014021
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2021.118123?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Mantas Plienis & Tomas Deveikis & Audrius Jonaitis & Saulius Gudžius, 2023. "Design of IOT-Based Framework for Evaluation of Energy Efficiency in Power Transformers," Energies, MDPI, vol. 16(11), pages 1-15, May.
    2. Chen Liang & Chang Chen & Weizhou Wang & Xiping Ma & Yuying Li & Tong Jiang, 2022. "Line Loss Interval Algorithm for Distribution Network with DG Based on Linear Optimization under Abnormal or Missing Measurement Data," Energies, MDPI, vol. 15(11), pages 1-16, June.
    3. Li Huang & Gan Zhou & Jian Zhang & Ying Zeng & Lei Li, 2023. "Calculation Method of Theoretical Line Loss in Low-Voltage Grids Based on Improved Random Forest Algorithm," Energies, MDPI, vol. 16(7), pages 1-16, March.

    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:eee:appene:v:306:y:2022:i:pb:s0306261921014021. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.