充电站可调度潜力是充电站参与电力市场投标策略优化的可行域空间，然而电动汽车接入时间的不确定性使得充电站可调度潜力难以准确评估。针对此，提出一种考虑电动汽车充电时间随机性的充电站可调度潜力不确定性分析方法。首先，基于闵可夫斯基求和理论建立了各类电动汽车集群的广义储能模型。其次，分析了电动汽车到站和离站时间随机性对充电站可调度潜力的影响，将离散化的电动汽车到站离站时间概率密度函数映射到电动汽车个体模型参数的概率分布，并结合电动汽车集群的广义储能模型得到各类电动汽车集群可调度潜力的概率特性。进一步，通过卷积运算加和各类电动汽车集群参数得到充电站的可调度潜力的概率分布特征。最后，在MATLAB中进行仿真验证，并与蒙特卡洛模拟进行对比，验证了所提方法的有效性。

The dispatchable potential of charging stations represents the feasible solution space for optimizing their bidding strategies in the electricity market. However, the uncertainty in the access times of electric vehicles complicates the accurate assessment of this dispatchable potential. To address this issue, an uncertainty analysis method was proposed for evaluating the dispatchable potential of charging stations, taking into account the stochastic nature of electric vehicle charging times. Firstly, a generalized energy storage model for various types of electric vehicle clusters was established using Minkowski summation theory. Secondly, the impact of the randomness in electric vehicle arrival and departure times on the dispatchable potential of charging stations was analyzed. The discretized probability density functions of these times were mapped to the probability distributions of individual electric vehicle model parameters. By integrating these with the generalized energy storage model of electric vehicle clusters, the probabilistic characteristics of the dispatchable potential across various electric vehicle clusters were derived. Furthermore, the probability distribution characteristics of the dispatchable potential of charging stations were derived by aggregating the parameters of various electric vehicle clusters using convolution operations. Finally, simulations were conducted in MATLAB and compared with Monte Carlo simulations to validate the effectiveness of the proposed method.