The integration of photovoltaic–energy storage systems (PV–ESS) facilitates not only the efficient utilization of solar-generated electricity but also significantly strengthens grid flexibility and resilience. As PV–ESS installations expand in scale and operational complexity, conventional optimization techniques increasingly encounter limitations in managing the highly dynamic and uncertain operating conditions, creating substantial challenges for coordinated system control. By examining the interaction mechanisms between PV and storage, this paper proposes a coordinated optimization algorithm based on a Stackelberg (leader–follower) game. A hierarchical decision framework is established, where the PV subsystem functions as the leader and the energy storage subsystem as the follower. The conventional centralized optimization approach is transformed into a game between two autonomous agents, with the game equilibrium determined through iterative optimization. By analyzing the benefit drivers and decision behaviors of both subsystems, the overall system performance is maximized. A case study demonstrates that the proposed Stackelberg strategy effectively regulates the storage charging and discharging process in a PV–ESS system. The approach reduces total operating costs while maintaining high storage efficiency, achieving an optimal balance between economic benefits and technical performance.
Lan et al. (Fri,) studied this question.