Dynamic Pricing and Low-carbon Economic Dispatch of Integrated Energy System Based on Stackelberg Game

Aiming at the role exchange between the energy supplier and the energy user in the park integrated energy system, and the strong constraints of the park’s low-carbon economic operation, we propose a hierarchical carbon trading mechanism considering dynamic parameters and a master-slave game optimization scheduling method for the park integrated energy system. First of all, the energy system operator (ESO) in the integrated energy system at the park level is set as the top leader and the integrated energy system parks are set as the bottom followers. The energy operators aim to maximize their own benefits, and guide the optimization of the lower level parks by setting the purchase and sale price, the carbon trading base price, and the price growth rate between the parks. The lower level parks respond to the price information released by the upper level with the goal of minimizing their operating costs; thus, the master-slave game model is constructed. Secondly, the low carbon economic operation constraints of the park level integrated energy system are fully taken into consideration, a ladder carbon trading mechanism is introduced after considering dynamic parameters into the game model to limit carbon dioxide emissions, and the demand response is introduced at the park side. Finally, the jellyfish search algorithm is used to optimize the purchase and sale electricity price, carbon trading base price and price growth rate published by the upper level, and CPLEX is used to optimize the equipment output, demand response, and purchase and sale plan of the lower level park. The simulation results show the effectiveness of the proposed model and method. © 2024 Science Press. All rights reserved.