论文标题
部分可观测时空混沌系统的无模型预测
Preemptive Scheduling of EV Charging for Providing Demand Response Services
论文作者
论文摘要
我们开发了一种新算法，用于在有限的地平线上安排大量电动汽车（EV）的充电过程。我们假设电动汽车到达具有不同充电水平和不同灵活性窗口的充电站。假定到达过程具有已知分布，并且电动汽车的充电过程可能是先发制人的。我们将调度问题提出作为一个有限的动态程序。我们表明，由此产生的公式导致一个单调动态程序，LIPSCHITZ连续值函数可与系统参数的扰动进行稳健。我们提出了一种基于仿真的拟合值迭代算法来确定值大约确定值的函数，并得出用于计算大约最佳解决方案的样品复杂性。
We develop a new algorithm for scheduling the charging process of a large number of electric vehicles (EVs) over a finite horizon. We assume that EVs arrive at the charging stations with different charge levels and different flexibility windows. The arrival process is assumed to have a known distribution and that the charging process of EVs can be preemptive. We pose the scheduling problem as a dynamic program with constraints. We show that the resulting formulation leads to a monotone dynamic program with Lipschitz continuous value functions that are robust against perturbation of system parameters. We propose a simulation based fitted value iteration algorithm to determine the value function approximately, and derive the sample complexity for computing the approximately optimal solution.
