基于分布鲁棒定价的集群风电场与共享储能两阶段优化运行

Two-stage Optimal Operation of Clustered Wind Farms and Shared Energy Storage Based on Distributionally Robust Pricing

  • 摘要: 在新型电力系统加速构建与电力市场化改革深度耦合的背景下,风电规模化入市,独立共享储能逐步成为市场化调节主体。针对出力不确定性加剧风电场市场履约风险,以及固定价格储能服务模式因缺乏激励制约利用率的问题,提出一种风电基地中集群风电场与共享储能的两阶段优化运行策略。首先,在日前阶段构建共享储能与集群风电场的主从博弈分布鲁棒定价模型,制定兼顾激励性与鲁棒性的储能服务价格;其次,在日内阶段基于日前定价结果,滚动优化集群风电场的租赁需求与共享储能充放电策略,提升运行灵活性与经济性;最后,为保障风电基地多风电场间的公平合作,设计考虑功率调节贡献率的改进Shapley值法将总成本合理分摊。结果表明,该策略可帮助风电厂降低市场履约风险,同时提升共享储能经济效益,为风电基地中多风电场合作运行与独立共享储能商业化运营提供可行路径。

     

    Abstract: Against the backdrop of the rapid development of the new-type power systems and their deep coupling with electricity market-oriented reforms, large-scale wind power is increasingly participating in market transactions, while independent shared energy storage is emerging as a key flexibility provider. To mitigate compliance risks caused by wind power uncertainty and the underutilization of fixed-price storage services, this study proposes a two-stage optimal operation strategy for clustered wind farms and shared energy storage within wind power bases. In the day-ahead stage, a distributionally robust leader-follower pricing model is established to determine service prices that balance both robustness and incentives. In the intraday stage, rolling optimization is applied to adjust wind farm leasing demand and charging–discharging strategies of the shared energy storage, thereby enhancing operational flexibility and economic efficiency. To ensure equitable cooperation among multiple wind farms, an improved Shapley value method that accounts for power regulation contributions is introduced to achieve equitable cost allocation. Case results demonstrate that the proposed strategy reduces compliance risks, enhances energy storage profitability, and offers a feasible pathway for the cooperative operation and commercialization of shared energy storage in wind power bases.

     

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