Probabilistic revenue analysis for electric vehicle charging
C Santoyo, S. Coogan
Conference on Control Technology and Applications (CCTA), 2022
Abstract
Electric Vehicle (EV) charging facilities operate under specific pricing models to mitigate the often random demands of arriving users while balancing their self-interested financial goals. In this paper, we study charging facilities operating with a discrete service level model. Here, users arrive randomly with a collection of random demands. In particular, an arriving user selects the service level, i.e., energy price and charging rate, that minimizes the total cost of receiving service. Upon selection, a portion of the service level cost faced by users, a function of the offered prices and rates, becomes revenue to the charging facility. To that end, we consider the case when a charging facility has a collection of charging rates to offer such that the respective prices maximize the expected revenue. First, we present an optimization program that yields the service level prices that maximize the expected revenue at a charging facility with consideration for the charging facility's operational costs. Then, we derive a high-confidence bound on the total revenue expected at a charging facility operating under the service level model. Lastly, we illustrate the application of the results via a numerical study.