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Capacity configuration of a hybrid energy storage system for the fluctuation mitigation and frequency regulation of wind power based on Aquila Optimizer and Variational Mode Decomposition

Author

Listed:
  • Wang, Jinjun
  • Wang, Xinyu
  • Chen, Heng
  • Gao, Yue
  • Chen, Honggang
  • Liu, Wenyi
  • Sun, Ying
  • Zhang, Lei

Abstract

In consequence of the considerable increase in renewable energy installed capacity, energy storage technology has been extensively adopted for the mitigation of power fluctuations and the support of wind farms in the provision of primary frequency response services. This study proposes a hybrid energy storage system (HESS) incorporating lithium batteries and flywheels, developing a joint economic optimization model that integrates both fluctuation mitigation and frequency regulation modules. The mitigation module enhances wind power stability while minimizing storage configuration costs through consideration of charge/discharge efficiency and state of charge (SOC), whereas the frequency regulation module maximises revenue potential based on capacity allocation results. The findings indicate that the positive fluctuations in wind power are reduced by 0.87 %, while the negative fluctuations are reduced by 39.79 %. The proportion of energy storage configurations with the best smoothing effect and economy of storage is reduced to 3.25 %. In response to the frequency regulation demands of wind farms, the standard electricity price is reduced by 7.24 %, while the standard electricity price for participating in frequency regulation and peak shaving services is decreased by 13.81 %. The internal rate of return for the optimal allocation scheme, considering the profit potential of energy storage, is as high as 16.82 %. This model provides an effective technical solution for the coordinated operation of multiple energy storage systems, as well as providing theoretical support for the large-scale development of hybrid energy storage systems.

Suggested Citation

  • Wang, Jinjun & Wang, Xinyu & Chen, Heng & Gao, Yue & Chen, Honggang & Liu, Wenyi & Sun, Ying & Zhang, Lei, 2025. "Capacity configuration of a hybrid energy storage system for the fluctuation mitigation and frequency regulation of wind power based on Aquila Optimizer and Variational Mode Decomposition," Energy, Elsevier, vol. 330(C).
    • Handle: RePEc:eee:energy:v:330:y:2025:i:c:s0360544225025368
    DOI: 10.1016/j.energy.2025.136894
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    References listed on IDEAS

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    1. Jiacheng Guo & Hao Wu & Tao Ma & Rongxin Yin & Yuekuan Zhou & Ji Li & Jinyue Yan & Jinqing Peng, 2026. "Scenario-adaptive hierarchical optimisation framework for design in hybrid energy storage systems," Nature Communications, Nature, vol. 17(1), pages 1-19, December.
    2. Lin, Yaoting & Zhou, Wei, 2026. "A stochastic cloud-driven clustering sizing method for a hybrid photovoltaic/battery energy system integrated with electric bus charge station: A case study for China," Energy, Elsevier, vol. 342(C).
    3. Yao, Qi & Liang, Zemin & Guan, Yuanpeng & Ke, Yiming & Hu, Yang & Fang, Fang & Liu, Jizhen, 2026. "Wake model-free active power control for wind-storage coordination using a state-decoupled MATD3 algorithm," Energy, Elsevier, vol. 347(C).

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