Dynamic Scheduling Optimization of Photovoltaic–Energy Storage Charging Station Considering Electric Vehicle Charging Guidance Strategy

The charging real-time tariff mechanism and electric vehicle (EV) charging guidance evaluation are designed to address the congestion and high operating cost problem of photovoltaic-energy storage charging station (PV-ES CS) during peak hours. First, a charging real-time tariff mechanism is proposed based on the historical congestion or idle situation of EV charging at PV-ES CS; second, an EV charging guidance evaluation is designed by comprehensively considering the EV spatial and temporal distributions, waiting time, and the amount of pending charging; and, finally, a multi-source cooperative scheduling strategy based on grid time-of-use (TOU) is designed. Within the charging price range acceptable to both parties, a pricing guidance model is established with the objectives of maximizing PV-ES CS revenues and minimizing users' EV charging costs, and the model is optimally solved by the Adaptive Particle Swarm Optimization (APSO) algorithm. Finally, a simulation analysis is carried out with a PV-ES CS in a region of Chongqing, and the results show that the established optimization model not only reduces the cost of PV-ES CS and user EV charging cost but also improves the revenue of PV-ES CS and PV utilization rate.