针对高比例新能源接入电力系统所引发的系统调频资源不足等问题，提出了一种基于虚拟电厂（virtual power plant，VPP）技术，聚合楼宇内灵活性资源，联合参与多能市场与调频辅助服务市场的两阶段优化方法。首先，构建了以智慧楼宇为单元的气电虚拟电厂模型。其次，考虑到楼宇内电储能和电动汽车作为优质的调频资源，设计了VPP辅助电网调频的日前-实时两阶段优化策略。在日前阶段，依据风光等预测信息，以VPP运行总成本最小化为目标函数，运用混合整数线性规划方法，获取日前全局最优调度方案；在实时阶段，根据调频信号等实测数据，采用模型预测控制结合混合整数二次规划进行滚动优化，以减小预测误差。最后在不同场景下对所提方法进行仿真验证，结果表明，VPP利用电储能和电动汽车辅助电网调频能够充分挖掘其灵活性潜力，实现资源在能量和调频市场上的最优配置，显著提升VPP的整体运行效益。

To address the issue of insufficient frequency regulation resources in power systems caused by high penetration of renewable energy, a two-stage optimization method is proposed based on virtual power plant （VPP） technology. This method aggregates flexible resources within buildings to jointly participate in multi-energy markets and frequency regulation ancillary service markets. Firstly, a gas-electric VPP model is constructed with smart buildings as units. Secondly, considering the high-quality frequency regulation potential of electric energy storage and electric vehicles within buildings, a day-ahead and real-time two-stage optimization strategy is designed for VPP-assisted grid frequency regulation. In the day-ahead stage, based on forecasts such as wind and solar generation, the mixed-integer linear programming method is applied to obtain the global optimal day-ahead scheduling scheme, aiming to minimize the total operating cost of the VPP. In the real-time stage, model predictive control combined with mixed-integer quadratic programming is used for rolling optimization based on real-time measurements such as frequency regulation signals, reducing prediction errors. Finally, simulation results under different scenarios demonstrate that the proposed method enables the VPP to fully exploit the flexibility potential of electric energy storage and electric vehicles for grid frequency regulation, achieving optimal resource allocation in both energy and frequency regulation markets while significantly improving the overall operational efficiency of the VPP.