Optimization of Multi Stakeholders in Urban Multi-Energy Systems from Game Perspective

Given the increasingly deep coupling between the power distribution network, transportation network, and gas distribution network in urban multi-energy systems, a non-cooperative game optimization model based on game theory is proposed in this paper. Firstly, each energy subsystem is treated as a player, with its energy purchase cost function being used as the payoff function, and competition is conducted by adjusting equipment scheduling strategies. Secondly, to enable energy prices to more effectively guide equipment output, a mechanism for price adjustment that comprehensively considers the total load of energy subsystems is introduced. Additionally, from the perspective of privacy preservation, an iterative optimization algorithm is proposed, in which only price and energy purchase information are exchanged between energy subsystems, and other data are not disclosed. Finally, it is demonstrated through simulation results that the proposed algorithm achieves rapid convergence while preserving the privacy of energy subsystems and significantly reducing load fluctuations.