Dynamic Charging Scheduling for Electric Vehicles Considering Real-Time Traffic Flow

The coupling between a power system and a traffic system concerned is strengthened by the increasing penetration of electric vehicles (EVs) as well as ever-growing employment of fast charging stations (FCSs). FCSs play an important role in linking these two systems, and their charging scheduling could have significant impacts on the security of power system operation, traffic flows and experience of EV drivers. The real-time traffic flow plays a critical role in the charging scheduling for EVs. In this paper, the driving behaviors of EVs are simulated by the microscopic traffic flow model (MTFM) with geographic distances among FCSs and EVs well taken into account, and then a bi-level dynamic charging scheduling model presented to determine the real-time charging strategy for EVs with objectives of optimally tracking the day-ahead scheduling and minimizing the waiting time cost of EVs. Finally, a coupled system including a modified 33-node distribution system and a 48-node traffic system is employed to demonstrate the essential features of the proposed method.