An Optimal Charge Framework Using Multivariate Copula for Day-ahead Scheduling of Electric Vehicle in Parking Lot Providing Power Markets

With the increase of electric vehicles (EVs), forecasting and modeling charging load in parking lots and charging stations have become more important than ever. one of the most challenging problems in the optimal charging process is modeling EV owners' behavior. With estimating EV parameters charging stations can buy and sell energy in power markets. In this article, an optimal charging framework for electric vehicles in charging parking lots is presented, which reduces the cost of charging electric vehicles. In this study, real-time and day-ahead markets are considered simultaneously, for estimating EV's behavior the copula distribution is used as a more accurate distribution to model the electric vehicles data. In the optimal charging process, V2G and G2V processes and battery degradation are also considered. The simulation results show that by accurately modeling the behavior of EVs, the parking lot can participate in both markets and perform the optimal charging process and pay less than other ways.