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The Real-Time Distributed Control of Shared Energy Storage for Frequency Regulation and Renewable Energy Balancing

Author

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  • Yuxuan Zhuang

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Xin Fang

    (Polytechnic Institute, Zhejiang University, Hangzhou 310015, China)

Abstract

With the increasing integration of renewable energy sources, distributed shared energy storage (DSES) systems play a critical role in enhancing power system flexibility, operational resilience, and energy sustainability. However, conventional scheduling methods often suffer from excessive communication burdens, limited scalability, and poor real-time responsiveness, especially when handling fast-changing frequency regulation signals and fluctuating renewable energy outputs. To address these challenges, this paper proposes a consensus-driven distributed online convex optimization method that enables a decentralized scheduling of energy storage units by leveraging the consensus algorithm for local decision-making while maintaining global consistency. Additionally, an adaptive event-triggered mechanism is designed to dynamically adjust the communication frequency based on system state variations, reducing redundant information exchange and ensuring convergence and stability in a fully distributed environment. Simulation results on the IEEE 14-bus test system show that the strategy reduces the communication load by 33–60% and improves the convergence speed by over 40% compared to baseline methods. It also demonstrates a strong adaptability to storage unit disconnection and reconnection. By enabling a fast and efficient response to grid services such as frequency regulation and renewable energy balancing, the proposed approach contributes to the development of intelligent and sustainable power systems.

Suggested Citation

  • Yuxuan Zhuang & Xin Fang, 2025. "The Real-Time Distributed Control of Shared Energy Storage for Frequency Regulation and Renewable Energy Balancing," Sustainability, MDPI, vol. 17(11), pages 1-27, May.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:11:p:4780-:d:1662205
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    References listed on IDEAS

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    3. Zhang, Shixu & Li, Yaowang & Du, Ershun & Fan, Chuan & Wu, Zhenlong & Yao, Yong & Liu, Lurao & Zhang, Ning, 2023. "A review and outlook on cloud energy storage: An aggregated and shared utilizing method of energy storage system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
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