Optimal Scheduling of Virtual Power Plant Based on Stackelberg Game in the Context of “Electricity-Carbon-Green” Market

In order to promote the transformation to a new power system in the context of China's energy reform, a large number of distributed energy sources are integrated into the grid in the form of virtual power plants as aggregators, which poses a considerable challenge to the grid entities. In this paper, we design a “power-carbon-green” joint trading market framework and propose a Stackelberg game based on the optimal scheduling method of virtual power plant, with virtual power plants as the leader and load aggregators as the followers. The Nash equilibrium solution is obtained by iterative genetic algorithm. Finally, the algorithm is verified on the MATLAB platform by calling the CPLEX solver, the experimental results prove the effectiveness of the model, and both the virtual power plant and the load aggregator can obtain more benefits through this model.