Optimal charging strategies for unidirectional vehicle-to-grid using fuzzy uncertainties

Vehicle-to-grid (V2G) is a way to effectively integrate electric vehicles (EVs) with the power system network. Unidirectional V2G is especially attractive because it is easily implementable and requires little additional hardware. An EV can be effectively charged during its parking time, and can potentially generate revenues for the EV owner. It can also provide services to the electrical grid through an aggregated scheme. The aggregator combines the capacity of many EVs and bids them into electricity markets. In this paper, a novel charging scheme is proposed that optimizes the charging of EVs and the bidding of ancillary service in the electricity market, considering the different market uncertainties using fuzzy set theory. The electricity market parameters are forecasted using ARIMA models. Simulations performed on a hypothetical group of EVs in the ERCOT area show the benefits of the proposed scheme.