Optimizing photovoltaic energy sharing: A novel framework based on Stackelberg games in distribution networks

Increasing photovoltaic utilization has highlighted the complexities of peer-to-peer energy sharing (P2PESh) in distributed networks. These networks' dynamic characteristic leads to identifying and exploring energy-sharing areas, which fosters the evolution of regional energy trade. The current study aims to address this complexity by proposing a novel energy-sharing framework based on the Stackelberg game paradigm. The energy-sharing acts as a leader, where the dynamic pricing method is applied to the energy-sharing regions (ESRs). The PVs are used to intelligently select energy-sharing zones and optimize the flexible loads. A comprehensive profit maximization model is proposed, in which a multi-zone pricing strategy and network usage fees are incorporated. The enhanced artificial lemming algorithm (EALA) is employed to optimize this problem to ensure the efficient exploration and exploitation of the solution space. A utility model is represented for buyers to inform the energy-sharing zone selection and load configuration. The study establishes the existence and uniqueness of the Stackelberg equilibrium within this framework to ensure stability in energy transactions. The effectiveness of the proposed framework is verified in the real-world system, which exhibits increased profits for energy-sharing providers, improved income for buyers, and enhanced grid stability. The effective management of PVs operation and integration into the grid significantly enhanced the framework's flexibility. This research underscores the potential of integrating P2PESh strategies into distribution networks and offers a sustainable and efficient solution for the growing community of solar subscribers.