A Stackelberg Game Model for Photovoltaic and Energy Storage Charging Station participates in the Electrical Spot Market

Abstract

The increasing integration of photovoltaic generation, energy storage, and electric vehicle charging infrastructure introduces new challenges for coordinated operation in grid-interactive energy systems. This study develops a bi-level Stackelberg game framework for photovoltaic-energy storage charging stations (PECS) participating simultaneously in day-ahead electricity and frequency-regulation ancillary service markets. A pre-clearing-based decision mechanism is introduced to coordinate interactions between charging stations and electric vehicle aggregators, enabling adaptive adjustment of charging demand, photovoltaic output, energy-storage scheduling, and market bidding strategies. The charging station operator acts as the leader by optimizing electricity pricing and multi-market participation strategies, while electric vehicles act as followers that dynamically respond to pricing signals to minimize charging costs. The resulting bi-level optimization problem is transformed into a mixed-integer linear programming formulation through Karush–Kuhn–Tucker conditions and solved efficiently. Three representative charging-station configurations with different photovoltaic-storage capacities and load characteristics are investigated. Simulation results demonstrate that the proposed framework improves charging coordination, enhances photovoltaic-energy storage utilization, increases revenues from electricity and frequency-regulation services, and strengthens system flexibility under varying market conditions. By establishing a coordinated decision architecture for distributed energy resources and demand-side response, the proposed method provides an engineering-oriented approach for adaptive energy scheduling, regulation-signal-responsive operation, and intelligent management of grid-connected energy systems.