Low‐Carbon Optimal Scheduling of Multiple Virtual Power Plants Based on Asymmetric Nash Bargaining

ABSTRACT To effectively investigate the structural discrepancies and complementary energy characteristics among multiple virtual power plants (VPPs), and to improve the economic efficiency, low‐carbon performance, and operational reliability of the multi‐agent system, this paper proposes a low‐carbon collaborative optimal operation strategy for multiple VPPs based on the asymmetric Nash bargaining solution. First, considering the interests of various VPP operators and users, a cooperative operation framework for multiple VPPs under the green certificate and carbon trading mechanism is constructed using Nash bargaining theory, which facilitates electric–thermal energy transactions among different VPPs. Second, the Latin hypercube scenario generation method and a fast backward reduction technique are employed to handle the uncertainties associated with renewable generation and load power. Third, accounting for the multidimensional contributions of each VPP, an asymmetric Nash bargaining mechanism based on energy contribution rates is designed to allocate the cooperative gains among VPPs. Finally, the alternating direction method of multipliers (ADMM) is adopted to protect the information privacy of each participant. Case study results demonstrate that the proposed strategy can enhance the overall operational benefits and carbon reduction performance of the system, while promoting stronger collaboration and fairness‐oriented benefit allocation among VPPs.