Queueing Theory-Based Optimal Decision-Making Model of Battery Energy Storage-Assisted Fast Charging Station Participating in Emergency Demand Response

With concerns about greenhouse gases emission in the transportation sector, governments all over the world favor the adoption of electric vehicle (EV), and advance the construction of charging facilities. The allocation of battery energy storage (BES) can improve the economics and flexibility of EV charging station. The emergency demand response (EDR) program is widely popular among consumers because of its flexibility and high incentive payments. In this paper, an optimal decision-making model of BES-assisted EV charging station participating in EDR is proposed. The queueing model is established to describe the EV charging station load profile, where the arrival rate and the service rate of EVs at the charging station is estimated through Poisson process and battery charging behaviors respectively. The mobility patterns of vehicles are generated via National Household Transportation Survey (NHTS) data set. EV charging station load profiles are obtained from the queueing analysis, and they are integrated in the proposed decision-making model with consideration of EDR for BES-assisted EV charging station. The feasibility of the model is validated in different case studies, and the result shows that the deployment of BES is beneficial to the optimal operation strategy of fast charging stations.