电动汽车与直流配电网协同的分布式自适应滚动预测调度

Distributed Adaptive Rolling Predictive Scheduling Based on Coordination of Electric Vehicles and DC Distribution Networks

为充分挖掘电动汽车(EV)的灵活调度潜力,提出了EV与直流配电网协同的分布式自适应滚动预测调度方法。首先,建立了电压源型换流器、储能及直流配电网潮流的数学模型;然后,构建了不可调度、只充电和可充放电3类EV充电偏好的数学模型,并以日电能损耗和弃光电量的加权和最小为目标建立了直流配电网自适应滚动预测调度模型,通过实时EV集群的取车时间动态更新调度窗口,以满足每辆EV的期望电量需求;最后,建立了直流配电网分布式滚动预测调度模型,并采用交替方向乘子法实现分布式求解,以解决集中式调度通信量大的问题。仿真结果表明,通过对EV与直流配电网灵活性资源的协同调度可显著降低电能损耗、提升分布式电源接纳能力,同时,所采用的分布式算法具有良好的收敛性能和计算速度。

In order to fully tap the flexible scheduling potential of electric vehicles (EVs), a distributed adaptive rolling predictive scheduling method based on the coordination of EVs and DC distribution networks is proposed. Firstly, the mathematical models of voltage source converter, energy storage and power flow of DC distribution networks are established. Then, the mathematical models of non-schedulable, charge-only and charge-discharge EV charging preferences are constructed, and the adaptive rolling predictive scheduling model of DC distribution networks is established with the goal of minimizing the weighted sum of daily energy loss and photovoltaic curtailment. The scheduling window is dynamically updated through the pick-up time of real-time EV clusters to meet the expected power demand of each EV. Finally, the distributed rolling predictive scheduling model of DC distribution networks is established, and the alternating direction method of multipliers is used to achieve distributed solution, so as to solve the problem of large communication traffic of centralized scheduling. The simulation results show that the cooperative scheduling of EV and DC distribution network flexibility resources can significantly reduce power loss and improve the acceptance capability of distributed power supply. At the same time, the distributed algorithm adopted has good convergence performance and computing speed.