针对分布式储能聚合参与电能量市场时个体效益保障不足、聚合可行域与运行目标不匹配、两阶段投标策略耦合性弱等问题，提出一种计及个体效益驱动的储能聚合方法及其两阶段市场投标策略。首先，基于卡罗需-库恩-塔克(Karush-Kuhn-Tucker，KKT)条件构建计及个体效益约束的储能聚合可行域优化模型，在保障各储能电站收益不低于独立参与市场的前提下实现多主体资源整合。然后，建立储能聚合商参与日前-实时两阶段市场的双层优化模型，在日前阶段刻画策略性报价行为，在实时阶段构建基于日前计划偏差的功率调整机制。基于博弈论分析市场均衡的存在性与唯一性，并提出两阶段市场出清方法。引入Roy Billinton测试系统仿真表明：所提聚合方法使4个聚合商合计收益较闵可夫斯基求和方法提升15.5%，异构性较强的聚合商收益提升达16.7%，两阶段市场合计收益较仅参与日前市场提升19%。该文方法能够在保障个体理性的前提下实现储能资源整合与收益提升，有效耦合日前策略性报价与实时灵活性调整，为分布式储能参与电力市场提供了理论依据与方法支撑。

To address the challenges in aggregated participation of distributed energy storage stations in electricity energy markets, including insufficient consideration of individual benefits, misalignment between aggregated feasible regions and operational objectives, and weak coupling of bidding strategies in two-stage markets, this paper proposes an individual benefit-driven aggregation method and a two-stage market bidding strategy for distributed energy storage. Firstly, based on Karush-Kuhn-Tucker (KKT) conditions, an optimization model for the aggregated feasible region incorporating individual benefit constraints is constructed, enabling multi-agent resource integration while ensuring that the revenue of each energy storage station is no less than that achieved through independent market participation. Subsequently, a bi-level optimization model for energy storage aggregators participating in day-ahead and real-time two-stage energy markets is established, characterizing strategic bidding behavior in the day-ahead stage and constructing a power adjustment mechanism based on day-ahead schedule deviations in the real-time stage. Based on game theory, the existence and uniqueness of market equilibrium are analyzed, and a two-stage market clearing method is proposed by transforming the bi-level optimization into a single-level KKT system. Simulation results on the Roy Billinton test system demonstrate that the proposed aggregation method increases the total revenue of four aggregators by 15.5% compared to the Minkowski summation method, with revenue improvements reaching 16.7% for aggregators with higher heterogeneity. The total revenue in the two-stage market is 19.0% higher than that achieved by participating only in the day-ahead market. The proposed method achieves energy storage resource integration and revenue enhancement while ensuring individual rationality, effectively coupling day-ahead strategic bidding with real-time flexibility adjustments, thereby providing theoretical foundations and methodological support for distributed energy storage participation in electricity markets.