ZHANG Sufang, YANG Zhengyi, MA Kuncheng, REN Zhongrui, WANG Yi
[Objective] This paper aims to tap into the regulation potential of electric vehicles （EVs） within multi-market environments， to address the critical issues of information asymmetry and scheduling deviations between aggregators and users， and construct an optimal scheduling model that balances the interests of multiple parties. [Methods] A three-layer "electricity market-aggregator-user" Stackelberg game model is established. In this framework， the aggregator acts as the leader to coordinate revenues from the energy market， frequency regulation market， and green electricity certificate transactions. To handle price uncertainties， a robust optimization approach has been employed. Furthermore， an incentive-compatible mechanism based on the Vickrey-Clarke-Groves （VCG） theory is designed to eliminate the motivation for users to misreport their private information. To enhance model accuracy， a non-linear battery degradation model is introduced， and the game equilibrium is solved using backward induction combined with professional linearization techniques. [Results] Case studies demonstrate that the proposed mechanism reduces the system peak load by 17.4% and lowers the comprehensive costs for users by 16.27%. The analysis verifies that truthful reporting of private information is the optimal strategy for users under the VCG-based incentive mechanism. Notably， the aggregator can reduce physical execution deviations by over 80% by conceding less than 10% of its potential profits， indicating a high efficiency in risk mitigation. [Conclusions] The VCG mechanism effectively achieves risk isolation on the user side. The coupling of multiple markets and the application of robust optimization significantly bolster the aggregator’s resilience against market volatility. Moreover， it is identified that a battery cost below 1000 CNY/kWh serves as the economic threshold for the large-scale deployment of vehicle-to-grid （V2G） applications.