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Optimal Configuration of Energy Storage Systems in High PV Penetrating Distribution Network

Author

Listed:
  • Jinhua Zhang

    (School of Electric Power, North China University of Water Resources and Electric Power, Zhengzhou 450045, China)

  • Liding Zhu

    (School of Electric Power, North China University of Water Resources and Electric Power, Zhengzhou 450045, China)

  • Shengchao Zhao

    (School of Electric Power, North China University of Water Resources and Electric Power, Zhengzhou 450045, China)

  • Jie Yan

    (State Key Laboratory of New Energy Power System, School of New Energy, North China Electric Power University, Beijing 100096, China)

  • Lingling Lv

    (School of Electric Power, North China University of Water Resources and Electric Power, Zhengzhou 450045, China)

Abstract

In this paper, a method for rationally allocating energy storage capacity in a high-permeability distribution network is proposed. By constructing a bi-level programming model, the optimal capacity of energy storage connected to the distribution network is allocated by considering the operating cost, load fluctuation, and battery charging and discharging strategy. By constructing four scenarios with energy storage in the distribution network with a photovoltaic permeability of 29%, it was found that the bi-level decision-making model proposed in this paper saves 2346.66 yuan and 2055.05 yuan, respectively, in daily operation cost compared to the scenario without energy storage and the scenario with single-layer energy storage. After accessing IEEE-33 nodes for simulation verification, it was found that the bi-level decision-making model proposed in this paper has a good inhibition effect on voltage fluctuation and load fluctuation after energy storage configuration. In addition, this paper analyzes the energy storage that can be accessed by photovoltaic distribution networks with different permeability and finds that when photovoltaic permeability reaches 45% and corresponding energy storage is configured, the economic and energy storage benefits of the system are the best.

Suggested Citation

  • Jinhua Zhang & Liding Zhu & Shengchao Zhao & Jie Yan & Lingling Lv, 2023. "Optimal Configuration of Energy Storage Systems in High PV Penetrating Distribution Network," Energies, MDPI, vol. 16(5), pages 1-21, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:5:p:2168-:d:1078481
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    References listed on IDEAS

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    1. Maharjan, Salish & Sampath Kumar, Dhivya & Khambadkone, Ashwin M., 2020. "Enhancing the voltage stability of distribution network during PV ramping conditions with variable speed drive loads," Applied Energy, Elsevier, vol. 264(C).
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    3. Kumar, Dhivya Sampath & Sharma, Anurag & Srinivasan, Dipti & Reindl, Thomas, 2019. "Stability implications of bulk power networks with large scale PVs," Energy, Elsevier, vol. 187(C).
    4. Waseem, Muhammad & Lin, Zhenzhi & Liu, Shengyuan & Zhang, Zhi & Aziz, Tarique & Khan, Danish, 2021. "Fuzzy compromised solution-based novel home appliances scheduling and demand response with optimal dispatch of distributed energy resources," Applied Energy, Elsevier, vol. 290(C).
    5. Jieran Feng & Hao Zhou, 2022. "Bi-Level Optimal Capacity Planning of Load-Side Electric Energy Storage Using an Emission-Considered Carbon Incentive Mechanism," Energies, MDPI, vol. 15(13), pages 1-18, June.
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    Cited by:

    1. Faris E. Alfaris & Faris Almutairi, 2024. "Performance Assessment User Interface to Enhance the Utilization of Grid-Connected Residential PV Systems," Sustainability, MDPI, vol. 16(5), pages 1-26, February.

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