Scheduling EV Charging Having Demand With Different Reliability Constraints
Shiping Shao, Hossein Sartipizadeh, Abhishek Gupta
Abstract
We develop a new algorithm, based on approximate dynamic programming, to efficiently schedule the charging processes of a large number of electric vehicles (EVs) with flexibility, which allows the EV charging service provider to charge the EVs between their minimum and target state of charge (SoC) within a time window. We assume that the charging demands have known distributions and the charging process of EVs can be scheduled preemptively. We model the scheduling problem as a dynamic program with state-dependent constraints and solve it utilizing the fitted value iteration. We propose a multi-stage decoupled algorithm to reduce the dimensions in the fitted value iteration to reduce the computation complexity, and provide sufficient conditions for achieving optimality.