Abstract: In view of the electric-thermal coupling coordinated optimization between energy service operators (ESOs) and virtual power plant (VPP) alliances, this paper constructs a time-periodic asymmetric energy mapping contribution function, and proposes a hybrid game optimization method combining the Stackelberg game and Nash bargaining theory to maximize the revenue of ESOs and realize the rational cost allocation of VPP alliances. The model sets ESOs as leaders and VPP alliances as followers, and decomposes the VPP optimization problem into two sub-problems: cost minimization and revenue redistribution based on Nash bargaining theory. A hybrid strategy combining the particle swarm optimization (PSO) algorithm and alternating direction method of multipliers (ADMM) is adopted for efficient solution. Simulation results show that the proposed method increases the revenue of ESOs by 27.3% and reduces the cost of VPP alliances by 11.5%, while effectively improving the consumption level of renewable energy and optimizing carbon emissions.