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风电出力的随机性及电动汽车充、放电的不确定性给电力系统运行带来了很大风险。如何从运行的角度度量该风险以及从风险角度对系统运行进行优化决策是当前面临的新问题。该文考虑电源与负荷的双随机性，定义了电力系统短期充裕性指标：动态风险备用(dynamic reserve at risk， DRaR)和动态条件风险备用(dynamic conditional reserve at risk，DCRaR)，并给出了其计算方法；以最大化DCRaR为目标，建立了电力系统短期充裕性多阶段决策模型，实现了在购电成本约束下，电力公司购买不同类型电源的配比决策和电动汽车调度方案优化；仿真分析了风电接入、购电成本以及电动汽车充电模式对系统短期充裕性的影响，结果证明了所提指标和模型的合理性。“,”The characteristics of randomness and uncertainty of wind power and electric vehicle (EV) charging and discharging increase the risk of power system operation. How to evaluate the operational risk and make an optimal decision based on this risk is of great importance. The short-term adequacy measuring indexes of power systems, i.e. Dynamic Reserve at Risk (DRaR) and Dynamic Conditional Reserve at Risk (DCRaR) were proposed with consideration of double randomness from generation and load. The calculation method of the indexes was proved mathematically. A multi-stage decision model for short-term adequacy of power systems was built with the objective of maximizing DCRaR. Under the restriction of a reasonable cost, it can solve the purchasing scheme of different kinds of energy and EV charging scheduling schemes of the electric company. Simulation tests were done to evaluate the influences of wind power integration, electricity purchase cost and EV charging modes on short-term adequacy of power systems. The results show that the proposed indexes and model are reasonable.