A Stackelberg game virtual power plant resource aggregation and dynamic pricing method based on high-quality sample point selection

Virtual power plants (VPPs), as a model for effectively aggregating and efficiently managing distributed energy resources, possess significant development potential in participating in electricity spot market transactions. In the context of the spot market, this paper proposes an integrated model for VPP resource aggregation and dynamic pricing. The proposed method aggregates the power of various distributed energy resources (DESs) using the Minkowski sum and employs the inscribed hyperbox approximation method to decouple and reduce the dimensionality of the actual adjustable power domain. Based on this, a one-leader-multi-follower game model between the operator and multiple VPPs is established, and a dynamic pricing method based on a multi-VPP Stackelberg game is proposed. During the iterative optimization process, high-quality sampling points are added to the original sample set to continuously refine the original model. The case study demonstrates that, through coordinated management by the distribution system operator (DSO) and energy sharing among the VPPs, the proposed method reduces DSO costs by 58.29% while lowering the average operating costs of the VPPs by 34.12%, thereby achieving a win–win outcome for both the VPPs and the DSO.