Online Optimal Charging Strategy for Electric Vehicles

This work investigates scheduling strategies for charging electric vehicles (EVs) in distribution grids. Our proposed scheduling strategy is realized as a moving window optimization scheme. By considering load and price forecasting and EVs’ power demand, this strategy optimizes the charging costs of an EV fleet with consideration of grid constraints. Its benefit is first demonstrated through simulation studies on workday and weekend scenarios. Furthermore, we discuss the impact of scheduling windows on the optimization result. Last, the impact of forecasting errors of energy prices on the optimization performance is quantitatively analyzed. The results show that the proposed strategy can optimally plan EV charging schedules with consideration of online information and uncertainties.