Data-Driven-Based Electric Vehicle Charging Stations Operation Considering Demand Price Sensitivity

The fast growth of electric vehicles (EVs) brings huge challenges for power network and charging facility operators, motivating many researchers to develop pricing models for instructing EV user charging behavior. To efficiently control the EV charging demand by using price signals, better knowledge of the EV charging demand price sensitivity is of vital importance. In this work, a data-driven approach is firstly developed to estimate the price sensitivity of EV charging demand from historical data without intervening in EV user charging behaviors. Then, an operating framework is proposed for a charging station (CS) that procures energy from a retailer to satisfy the EV charging demand. To minimize the deviation cost in the real-time operation, a pricing method is further proposed by using the estimated price sensitivity of EV charging demand. Numerical simulations suggest that the proposed methods can satisfactorily predict the demand change in response to price signals and improve the profitability of the considered CS.