Optimal Scheduling Strategy of Virtual Power Plant Group Based on Master-Slave Game in Electric and Carbon Market

Under the background of electricity market and carbon market, with the deepening of research on virtual power plants and the interaction of electric energy in each region of the same regional power grid, an optimal scheduling strategy of virtual power plant group based on master-slave game under electric carbon market is proposed. Firstly, a virtual power plant group interaction framework is designed, in which the system operator sets the carbon price of electricity price, and each virtual power plant operator sets the operation plan according to the price. Secondly, based on the master-slave game, a virtual power plant group optimal scheduling model is established. Finally, particle swarm algorithm nested CPLEX solver is used to deal with the problem. The numerical results show that the proposed method not only promotes the utilization rate of distributed resources, but also increases the economic benefit of system operators by $\mathbf{2 8. 9 \%}$.