城市电网中的工业园区及商业园区具有电动汽车、空调等大量柔性资源，但受到运营条件及盈利主体差异约束，增加了协调调控难度。现有研究提出共享储能与多用户的博弈模型，但未考虑各园区柔性资源禀赋对价格博弈的影响，系统效益仍有提高空间。针对上述问题，本文建立电动汽车、空调等海量微资源参与系统冲击功率响应的柔性模型，提出以共享储能为框架的城市电网多园区柔性资源双层博弈调控策略，将商业园区及工业园区中的柔性资源纳入博弈策略，并影响共享储能定价策略。进一步提出自适应梯度双层迭代求解算法求解所提双层博弈模型。对比算例表明，相比现有共享储能博弈方法，所提方法能够充分利用各园区柔性资源，大幅提高共享储能收益，有效降低园区综合成本；相比启发式算法，所提双层迭代求解算法，具有更高求解效率及收敛速度。

Industrial parks and commercial parks in urban power grids possess substantial flexible resources, including electric vehicles (EVs) and air conditioners (ACs). However, operational constraints and divergent profit motives among stakeholders complicate coordinated control. Existing research has proposed game-theoretic models for shared energy storage interacting with multiple users, yet these models often neglect the influence of flexible resource endowments across different parks on price competition, leaving room for improving overall system benefits. To address these challenges, this paper establishes a flexibility model enabling massive micro-resources to participate in system impact power response. A two-layer game-theoretic control strategy for flexible resources in multi-park urban grids is proposed, utilizing a shared energy storage framework. This strategy incorporates the flexible resources from both commercial and industrial parks into the game formulation and influences the pricing strategy of shared energy storage. Furthermore, an adaptive gradient-based bi-level iterative solution algorithm is developed to solve the proposed bi-level game model. Comparative case studies demonstrate that, compared to existing shared energy storage game methods, the proposed approach can fully leverage the flexible resources within each park, markedly enhancing shared storage revenue and effectively reducing the comprehensive operational costs for the parks. Additionally, the proposed algorithm exhibits superior solving efficiency and convergence speed compared to heuristic algorithms.