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