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Energy Loss Reduction for Distribution Networks with Energy Storage Systems via Loss Sensitive Factor Method

Author

Listed:
  • Xiangming Wu

    (State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050021, China)

  • Chenguang Yang

    (State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050021, China)

  • Guang Han

    (State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050021, China)

  • Zisong Ye

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China)

  • Yinlong Hu

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China)

Abstract

The loss of distribution networks caused by various electrical motors including transformers and generators can significantly affect the efficiency and economical operation of the power grid, especially for new power systems with high penetration of renewable energies. In this paper, the potential of using an energy storage system (ESS) for loss reduction is investigated, where a novel two-stage method for key-bus selection and ESS scheduling is proposed. At the first stage, the most sensitive key buses to the variation of load are selected by using the loss sensitive factors (LSF) method. At the second stage, ESS scheduling is conducted by solving an optimization problem with uncertainties caused by high penetration of renewable energies, where the uncertainties are characterized by confidence levels. The optimal scheduling of ESS including locations, capacities, and working modes are obtained at the second stage. The effectiveness of the proposed method is demonstrated via numerical simulations. The influences of capacities of ESS and confidence levels with respect to uncertainties are also analyzed. It is demonstrated that the loss-reduction performances can be improved if the ESSs are deployed on the buses selected by the LSF method and operated under the developed optimal scheduling method.

Suggested Citation

  • Xiangming Wu & Chenguang Yang & Guang Han & Zisong Ye & Yinlong Hu, 2022. "Energy Loss Reduction for Distribution Networks with Energy Storage Systems via Loss Sensitive Factor Method," Energies, MDPI, vol. 15(15), pages 1-15, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:15:p:5453-:d:873640
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    References listed on IDEAS

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    1. Ruiyang Jin & Jie Song & Jie Liu & Wei Li & Chao Lu, 2020. "Location and Capacity Optimization of Distributed Energy Storage System in Peak-Shaving," Energies, MDPI, vol. 13(3), pages 1-15, January.
    2. Jihua Xie & Chang Chen & Huan Long & Long Wang, 2021. "A Loss Reduction Optimization Method for Distribution Network Based on Combined Power Loss Reduction Strategy," Complexity, Hindawi, vol. 2021, pages 1-13, July.
    3. Passey, Robert & Spooner, Ted & MacGill, Iain & Watt, Muriel & Syngellakis, Katerina, 2011. "The potential impacts of grid-connected distributed generation and how to address them: A review of technical and non-technical factors," Energy Policy, Elsevier, vol. 39(10), pages 6280-6290, October.
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    Cited by:

    1. Xiangming Wu & Nan Song & Jifeng Liang & Ye Lv & Zitian Wang & Lijun Yang, 2024. "High-percentage new energy distribution network line loss frequency division prediction based on wavelet transform and BIGRU-LSTM," PLOS ONE, Public Library of Science, vol. 19(8), pages 1-22, August.
    2. Chintan D. Patel & Tarun Kumar Tailor & Samyak S. Shah & Gulshan Sharma & Pitshou N. Bokoro, 2025. "Techno-Economic Enhancement of Distribution Network by Optimal DG Allocation Along with Network Reconfiguration Considering Different Load Models and Levels," Energies, MDPI, vol. 18(12), pages 1-16, June.

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