Optimal Scheduling Strategy of Virtual Power Plant Based on Bi-level Master-Slave Game

At present, distributed renewable energy and flexible resources such as energy storage and demand response are rapidly developing. Virtual power plants efficiently integrate distributed resources through control technology, which can improve the efficiency of distributed energy generation. Virtual power plants in the electricity market belong to various investors, forming a multi-party game pattern in the market. According to investors’ investment preferences, virtual power plants will be composed of resources with different flexibility. The article constructs a dual level master-slave game model between operators and multiple virtual power plants to balance the interests of multiple parties. Considering the mutual influence between upper level pricing and lower level output, this paper studies the dynamic price setting of operators and the optimization operation scheduling problem of virtual power plants. The lower level establish a multi virtual power plant optimization scheduling model, which aims to minimize the operating costs of each virtual power plant. The upper level aims to maximize the profit of the operator and dynamically formulate the purchase and sale price of virtual power plants based on the lower level output plan. It has been verified that the model can balance the interests of multiple parties while effectively improving the revenue of operators and reducing the operating costs of virtual power plants.