随着“双碳”目标的提出，构建清洁、高效的电力系统能源体系已然成为未来的发展趋势。然而，风、光等可再生能源大规模并网在缓解能源环境危机的同时，其出力的强不确定性也会导致严重的弃风弃光现象。合理地配置储能容量有利于实现清洁能源大规模消纳并提升系统经济性。因此，提出一种考虑多源协同与源荷不确定性的混合储能最优配置方法。首先，采用蒙特卡洛法实现场景生成并基于概率距离的快速前代消除法实现场景削减。然后，从系统经济性最优的角度出发，构建了储能规划-多能源运行随机双层优化模型，上层规划模型决策锂电池储能和抽水蓄能最佳的容量配置，下层运行模型进行风光储多类型能源的多时间尺度协调调度。所建立的规划-运行模型采用双层迭代策略求解，得出多场景下的最优的锂电池与抽水蓄能储能容量配置。最后，以浙江某新能源基地为例进行算例分析，验证了所提方法在提高系统经济性和新能源消纳方面的有效性。

With the introduction of the “dual carbon” targets, building a clean and efficient power and energy system has become necessary. However, while the large-scale grid-connected renewable energy such as wind and solar power alleviates the energy and environmental issues, the strong uncertainty of their output also leads to significant wind and solar power curtailment. Reasonable sizing of energy storage is crucial to improve the utilization of renewable energy and whole system economics. This paper proposes an optimal configuration method for hybrid energy storage considering multi-energy coordination and source-load uncertainty. First, a probability distance-based fast forward selection method reduces scenarios to represent uncertainty characterization. Then,from the perspective of optimal system economics, a bi-level stochastic optimization model integrating energy storage planning and multi-energy operation is established: the upper-level planning model determines optimal capacity configuration for battery and pumped hydroelectric storage, while the lower-level operational model coordinates the multi-timescale dispatch of wind, solar, and storage resources. The model was solved using an iterative strategy to determine optimal capacity configuration of battery and pumped hydroelectric energy storage considering multiple scenarios. Finally, the proposed method was validated through case studies on the Zhejiang power system to demonstrate its effectiveness in improving system economic efficiency and renewable energy utilization.