With the development of smart grid communication infrastructures, the two-way communication enables virtual power plants (VPPs) to participate in the market competition by aggregating distributed energy and controllable loads across regions for collaborative optimization and scheduling. The traditional aggregation and scheduling optimization of a single VPP is solved by centralized algorithm, while the real-time pricing (RTP) game competition among multiple VPPs is still a challenge. In this paper, we develop a multi-leader and multi-follower (MLMF) Stackelberg game model to formulate the interactions between multiple VPPs and energy consumers, to obtain the optimal strategies of VPP price and consumer power demand. Then, alternating direction method of multiplier (ADMM)-based strategy decision optimal algorithm is devised to achieve the equilibrium solution of the formulated game with only local information. Simulation results demonstrate that the utilities of both VPPs and energy consumers converge quickly, VPPs can achieve higher utility than fixed pricing strategy.