A Dynamic Pricing–Driven Bi‐level Coordinated Operation Planning Method for Integrated Photovoltaic–Storage–Charging Stations

ABSTRACT

In recent years, electric vehicle (EV) charging stations that integrate photovoltaic (PV) systems with energy storage have experienced rapid development. Consequently, new challenges have emerged in the integration of renewable energy and the optimal allocation of charging station capacities. This paper proposes an operation scheduling method for integrated photovoltaic‐storage‐charging stations (IPSCS) driven by dynamic pricing. In this methodology, a bi‐level optimisation framework is established. The upper‐level model, taking EV charging users as primary agents, aims to minimise charging costs through demand response to dynamic pricing strategies while optimising load distribution in the IPSCS. The lower‐level model focuses on the IPSCS operator perspective, seeking optimal capacity planning to achieve minimal equivalent annualised investment costs. From the planning perspective of IPSCS, an hourly annual PV generation profile is constructed from meteorological inputs to preserve the seasonal and intraday variability required for capacity planning. Furthermore, Monte Carlo simulation is employed to probabilistically model EV charging demand patterns, addressing uncertainties in charging demand projections that might compromise planning accuracy. From the operational standpoint, a fuzzy membership function is employed to classify the peak and valley periods of PV generation, which serves as the basis for dynamic pricing. Subsequently, a demand response mechanism is utilised to optimise the post‐response load distribution. This study employs a particle swarm optimisation (PSO)‐based approach to solve the model, with case simulations verifying its effectiveness in reducing peak‐valley load differences, decreasing PV curtailment rates, and enhancing charging station economic performance. Under the pricing assumptions, the archived case study yields an optimised configuration of 411 PV units and 1345 energy storage system (ESS) units, while the annual charging expenditure of EV users decreases by 67.34% relative to the baseline case.