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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
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    Citations

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    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.
    4. 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.

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