Optimal Operation of Fast Charging Station Aggregator in Uncertain Electricity Markets Considering Onsite Renewable Energy and Bounded EV User Rationality

The increasing proliferation of electric vehicles (EVs) and renewable energy sources (RESs) poses challenges to the operation of coupled power and transportation networks due to their uncertainties, where EV users' routing and charging behaviors are subjected to their complex decision-making rationality. To economically manage numerous fast charging stations with onsite RESs, this article focuses on the optimal day-ahead bidding and intraday scheduling strategies of a fast charging station aggregator (FCSA) to maximize its profit in the electricity market. Traffic simulation based on boundedly rational dynamic user equilibrium is presented to model charging demand under bounded rationality of EV users. To efficiently manipulate large-scale EVs, a group charging scheduling framework is proposed to reduce decision variables. Uncertainties in electricity prices, RES generation, traffic demand, and user rationality are addressed by stochastic programming. Case studies have validated the effectiveness of the proposed method in reducing the FCSA's operational costs and RES curtailment.