IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i7p2971-d1106415.html
   My bibliography  Save this article

Calculation Method of Theoretical Line Loss in Low-Voltage Grids Based on Improved Random Forest Algorithm

Author

Listed:
  • Li Huang

    (School of Electrical Engineering, Southeast University, Nanjing 211189, China)

  • Gan Zhou

    (School of Electrical Engineering, Southeast University, Nanjing 211189, China)

  • Jian Zhang

    (Guangdong Power Grid Co., Guangzhou 510600, China)

  • Ying Zeng

    (Guangdong Power Grid Co., Guangzhou 510600, China)

  • Lei Li

    (School of Electrical Engineering, Southeast University, Nanjing 211189, China)

Abstract

Theoretical line loss rate is the basic reference value of the line loss management of low-voltage grids, but it is difficult to calculate accurately because of the incomplete or abnormal line impedance and measurement parameters. The traditional algorithm will greatly reduce the number of samples that can be used for model training by discarding problematic samples, which will restrict the accuracy of model training. Therefore, an improved random forest method is proposed to calculate and analyze the theoretical line loss of low-voltage grids. According to the Influence mechanism and data samples analysis, the electrical characteristic indicator system of the theoretical line loss can be constructed, and the concept of power supply torque was proposed for the first time. Based on this, the attribute division process of decision tree model is optimized, which can improve the limitation of the high requirement of random forest on the integrity of feature data. Finally, the improved effect of the proposed method is verified by 23,754 low-voltage grids, and it has a better accuracy under the condition of missing a large number of samples.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:7:p:2971-:d:1106415
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/7/2971/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/7/2971/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Yonggang Wang & Fuxian Li & Ruimin Xiao & Nannan Zhang, 2024. "A Systematic Investigation into the Optimization of Reactive Power in Distribution Networks Using the Improved Sparrow Search Algorithm–Particle Swarm Optimization Algorithm," Energies, MDPI, vol. 17(9), pages 1-22, April.
    3. 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.

    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:7:p:2971-:d:1106415. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.