Stackelberg game-based multi-energy pricing and dispatch optimization for integrated energy systems

In the context of dual carbon goals， this paper proposes a multi-energy pricing and dispatch optimization strategy for integrated electricity-heat energy systems in an industrial park， based on the Stackelberg game to address low-carbon scheduling issues. Firstly， the paper introduces the transaction model between the park operator and the users. Secondly， a Stackelberg game model is developed， with the park operator acting as the leader and the user loads within the park acting as followers. The park operator model incorporates a tiered carbon trading mechanism， while the user load model considers the users’ electricity and heat demand response. Finally， the beetle antennae search-improved particle swarm optimization （BAS-PSO） algorithm and the CPLEX solver are utilized to determine the park operator’s pricing strategy and the users’ energy consumption strategies. Simulation results demonstrate that the proposed optimization strategy effectively balances the interests of all parties， resulting in a reduction in the peak-to-valley difference of user loads and a decrease in carbon emissions.