  Recent proliferation in electric vehicles (EVs) are posing profound impacts
over the operation of electrical grids. In particular, due to the physical
constraints on charging stations' capacity and uncertainty in charging demand,
it becomes an emerging challenge to design high performance scheduling
algorithms to better serve charging sessions. In this paper, we design a
predictive charging controller by actively incorporating each EV's
state-of-charge (SOC) information, which has strong effects on the utilization
of dispatchable power during peak hours. Simulation results on both synthetic
and real-world EV session and charging demand data demonstrate the proposed
algorithm's benefits on maximizing charging throughput and achieving higher
rate of feasible charging sessions while satisfying battery and station
physical constraints at the same time.
