An Exponential Cone Programming Approach for Managing Electric Vehicle Charging

Abstract

In “An Exponential Cone programming Approach for Managing Electric Vehicle Charging,” Chen, He, and Zhou propose a novel ECP approach to solving large-scale optimization of electric vehicle charging in public stations such as EVgo. Other than the stochastic arrivals of customers with different arrival/departure times and charging requirements, charging stations routinely incur high demand charges, costs related to the highest per-period total electricity used in a billing cycle, which can be as high as 70% of the total electricity bill. For the case with unlimited chargers, the authors characterize the theoretical performances of the ECP approach. For the case with limited chargers, the authors construct an ECP leveraging the idea from distributionally robust optimization and show in a data-calibrated numerical study that it performs better than common approaches, considering many practical implementation issues. The authors’ method of constructing ECPs can be potentially applicable to approximate more general two-stage stochastic programs.