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Hierarchical control strategy of wind-storage frequency support for SOC recovery optimization and arbitrage revenue

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Listed:
  • Pei, Ming
  • Wang, Qiheng
  • Ye, Lin
  • Luo, Yadi
  • Sha, Licheng
  • Zhang, Zaichi
  • Song, Xuri

Abstract

With the continuous increase in the penetration rate of renewable energy, the frequency stability of the power system is gradually declining. Hence, this paper proposes a hierarchical coordinated control strategy of the wind farm (WF) and the battery energy storage system (BESS) to provide frequency support. The strategy includes the upper-layer frequency regulation (FR) optimization strategy and the lower-layer state of charge (SOC) recovery optimization strategy. At first, the upper-layer control strategy uses model predictive control (MPC) to allocate power commands to the WF and BESS, enabling them to provide coordinated frequency support while fully utilizing the WF's reserve capacity. Then, it transfers the information of SOC changes to the lower-layer. Subsequently, the lower-layer control strategy converts the changes of SOC into charging and discharging commands within specific time domains to restore the SOC of the BESS and generate arbitrage income. This layer minimizes the power purchase cost and the depth of discharge (DOD), optimizing the SOC recovery process. Finally, the strategy's effectiveness is verified using an IEEE 9-bus system and an IEEE 39-bus system. Numerical results demonstrate that the proposed strategy reduces the maximum frequency deviation (MFD) by 8.75%–9.20% and increases total revenue by 12.68%–19.16% in the IEEE 9-bus system, and the strategy can reduce the MFD by 4.00%–6.14% and increase total revenue by 19.62%–28.74% in the IEEE 39-bus system compared with other FR control strategies. Moreover, the strategy enables the SOC to return to its initial value along an optimized path.

Suggested Citation

  • Pei, Ming & Wang, Qiheng & Ye, Lin & Luo, Yadi & Sha, Licheng & Zhang, Zaichi & Song, Xuri, 2024. "Hierarchical control strategy of wind-storage frequency support for SOC recovery optimization and arbitrage revenue," Applied Energy, Elsevier, vol. 365(C).
  • Handle: RePEc:eee:appene:v:365:y:2024:i:c:s0306261924006123
    DOI: 10.1016/j.apenergy.2024.123229
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    References listed on IDEAS

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    1. Guannan He & Qixin Chen & Panayiotis Moutis & Soummya Kar & Jay F. Whitacre, 2018. "An intertemporal decision framework for electrochemical energy storage management," Nature Energy, Nature, vol. 3(5), pages 404-412, May.
    2. Wang, Kaifeng & Ye, Lin & Yang, Shihui & Deng, Zhanfeng & Song, Jieying & Li, Zhuo & Zhao, Yongning, 2023. "A hierarchical dispatch strategy of hybrid energy storage system in internet data center with model predictive control," Applied Energy, Elsevier, vol. 331(C).
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