基于Stackelberg博弈与VCG机制的电动汽车聚合商鲁棒定价与优化调度

张素芳; 杨政益; 马琨程; 任中睿; 王怡

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基于Stackelberg博弈与VCG机制的电动汽车聚合商鲁棒定价与优化调度

张素芳¹, 杨政益², 马琨程², 任中睿¹, 王怡¹

作者信息 +

Robust Pricing and Optimal Scheduling for Electric Vehicle Aggregators Based on Stackelberg Game and VCG Mechanism

ZHANG Sufang¹, YANG Zhengyi², MA Kuncheng², REN Zhongrui¹, WANG Yi¹

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摘要

【目的】 为挖掘多市场环境下电动汽车（electric vehicle, EV）调节潜力,解决聚合商与用户间信息不对称及调度偏差问题,构建兼顾多方利益的优化调度模型。【方法】 建立“电力市场-聚合商-用户”三层Stackelberg博弈模型。聚合商作为领导者,统筹电能量、调频及绿色电力证书收益,采用鲁棒优化应对价格波动;设计基于维克里-克拉克-格罗夫斯（Vickrey-Clarke-Groves, VCG）的激励相容机制消除用户虚报动机;引入非线性电池损耗模型,利用逆向归纳法与线性化技术求解博弈均衡。【结果】 算例表明,所提机制使系统峰值负荷降低17.4%,用户综合成本下降16.27%;验证了如实上报私有信息为用户最优策略;聚合商仅需让渡不足10%的利润即可降低80%以上物理执行偏差。【结论】 VCG机制有效实现了用户侧风险隔离;多市场耦合与鲁棒优化显著提升了聚合商抗风险能力;明确了电池成本低于1000元/kWh为车网互动（vehicle-to-grid, V2G）规模化应用的经济临界点。

Abstract

[Objective] This paper aims to fully harness the regulation potential of electric vehicles (EVs) within multi-market environments. The study proposes an optimal scheduling model that balances the interests of multiple stakeholders to resolve the critical issues of information asymmetry and scheduling deviations between aggregators and users. [Methods] A three-layer "electricity market-aggregator-user" Stackelberg game model was established. In this framework, the aggregator acted 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 was employed. Furthermore, an incentive-compatible mechanism based on the Vickrey-Clarke-Groves (VCG) theory was designed to eliminate the motivation for users to misreport their private information. To enhance model accuracy, a non-linear battery degradation model was introduced, and the game equilibrium was solved using backward induction combined with professional linearization techniques. [Results] Simulation results 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 dominant 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 study concludes that the VCG mechanism effectively achieves risk isolation on the user side, ensuring fair participation. The coupling of multiple markets and the application of robust optimization significantly bolster the aggregator’s resilience against market volatility. Moreover, the findings clarify that a battery cost below 1000 CNY/kWh serves as the economic tipping point for the large-scale deployment of vehicle-to-grid (V2G) applications.

导出引用

张素芳, 杨政益, 马琨程, 任中睿, 王怡. 基于Stackelberg博弈与VCG机制的电动汽车聚合商鲁棒定价与优化调度[J]. 电力建设. 0

ZHANG Sufang, YANG Zhengyi, MA Kuncheng, REN Zhongrui, WANG Yi. Robust Pricing and Optimal Scheduling for Electric Vehicle Aggregators Based on Stackelberg Game and VCG Mechanism[J]. Electric Power Construction. 0

中图分类号： TM73

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