Robust stackelberg game strategies for managing demand uncertainty in energy trading problems

Abstract

Peer-to-peer (P2P) energy trading is emerging as a promising approach for facilitating energy sharing among microgrids. This paper addresses the P2P energy trading problem using a robust Stackelberg game (RSG) approach, where producers and consumers are modeled as multiple leaders and followers, respectively, within a power system, while accounting for demand uncertainty. The robust noncooperative framework treats the energy trading problem as a competitive game among self-interested prosumers, each selecting a demand strategy to maximize their own benefit. The study also incorporates the impact of carbon emissions and transmission costs. To solve the social welfare function, a dual decomposition method is employed. Simulation results demonstrate the convergence performance, fairness, and scalability of the proposed decentralized approach for market clearing in P2P energy trading scenarios. The findings reveal that the method not only reduces trading costs for consumers and enhances utility for producers but also increases producer profits by $34.56\%$ compared to conventional methods.