Stackelberg game for shared energy storage and wind farm bilateral trading with multi-market participation

Xingxu Zhu, Guiqing Zhao, Junhui Li, Haojun Liu, Zhiqiang Zhao, Cuiping Li, Zhi Li and Hongwei Zhou

Energy, 2025, vol. 326, issue C

Abstract: To address the high investment costs, low utilization, and long payback periods of single-service energy storage, this study proposes a shared energy storage strategy integrating wind-storage bilateral transactions and ancillary peak-shaving services. By leveraging multi-service synergy, the strategy improves energy storage utilization and economic benefits while optimizing WF's bidding strategies in the day-ahead market. A revenue maximization model is developed based on the Weibull distribution of wind power, incorporating capacity degradation costs. A Stackelberg game framework is formulated to determine optimal participation strategies for shared energy storage operators (SESO) and WFs, solved using a hybrid approach that combines an improved genetic algorithm and an interior-point method. Case studies demonstrate that, compared to single leasing, the proposed model increases SESO and WF benefits by 2.35 %, 5.69 %, and 6.81 %, respectively, while SESO revenue rises by 255.46 % compared to ancillary services alone. Additionally, the model reduces WF leasing costs, mitigates wind curtailment and grid deviation penalties, and enhances overall economic efficiency. This study provides a structured framework for wind-storage collaboration, offering theoretical insights into optimizing energy storage participation in electricity markets and supporting the advancement of smart grids and renewable energy integration.

Keywords: Shared energy storage; Wind power uncertainty; Energy market; Ancillary peak-shaving market; Stackelberg game (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:326:y:2025:i:c:s0360544225018808

DOI: 10.1016/j.energy.2025.136238

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