考虑规模化电动汽车与风电接入的随机解耦协同调度

大规模电动汽车并网和风电出力的随机性增加了电力系统安全经济运行的难度。针对风电出力难以预测的特点,同时兼顾电网侧和电动汽车聚合商侧的运行效益,建立了风电、火电以及电动汽车鲁棒双层随机优化调度模型。为了提高求解效率,基于近似Benders算法构建了电动汽车与电网之间的互动关系。此外,针对规模化电动汽车之间难以协同优化的问题,运用辅助问题原理对电动汽车个体之间的耦合关系进行了解耦,将电动汽车群的联合优化转化成为单辆电动汽车调度的并行计算,实现了对电动汽车个体的调度。最后,针对改进的IEEE 39节点算例进行了仿真分析,验证了所提模型和算法的有效性。

Stochastic Decoupling Collaborative Dispatch Considering Integration of Large-scale Electric Vehicles and Wind Power

The randomness of large-scale electric vehicles (EVs) connected to power grid and wind power output increases the difficulty of safe and economic operation of power system. In view of the unpredictable characteristics of wind power output and considering operational benefits of system and EV aggregators, a robust two-layer stochastic optimal dispatch model of wind power, thermal power and EVs is established. In order to improve the solution efficiency, the interaction between EVs and power grid is constructed based on the approximate Benders algorithm. In addition, in order to solve the problem of difficult coordination and optimization between large-scale EVs, the coupling relationship between individual EVs is coupled by the auxiliary problem principle, and the joint optimization of EV groups is transformed into the parallel computation of a single EV dispatch, which realizes the individual dispatch of EV. Finally, the simulation analysis of the improved IEEE 39-bus system is carried out to verify the effectiveness of the proposed model and algorithm.