为实现“双碳”战略目标，针对多元负荷及可再生能源预测误差大导致的综合能源系统（integrated energy system，IES）运行不稳定、碳排放量高的问题，提出一种考虑源-荷多元预测及绿证-阶梯碳交易的综合能源系统优化调度方法。建立了一种奖惩阶梯型碳交易机制，通过统一分配配额与惩罚性碳价相结合，实现绿证-阶梯碳的联合交易。为提升源-荷多元预测精度，构建了基于TOC-VMD-SSA-LSTM的组合预测模型，同时考虑电转气（power to gas，P2G）两阶段运行，建立了以总成本最小为优化目标的多能耦合的IES主动调度模型。结果表明：本文所提预测模型的平均绝对误差、均方根误差分别降低了1.44%、3.94%，拟合系数提高了1.18%；在采用绿证-阶梯碳联合交易并耦合两阶段电转气设备后，IES总碳排放量与调度成本较单一基础场景分别降低了13.95%和9.27%。

To achieve the "dual carbon" strategic goal and address the challenges of unstable operation and high carbon emissions in integrated energy system (IES) caused by significant forecasting errors in multiple loads and renewables, an optimal scheduling method for IES is proposed, considering multi-source load forecasting and green certificate-stepped carbon trading. A reward and punishment stepped carbon trading mechanism is established, which synergizes dynamic quota allocation with punitive carbon pricing to realize green certificate-stepped carbon joint trading. To enhance the accuracy of multi-source load forecasting, a combined forecasting model based on TOC-VMD-SSA-LSTM is constructed. Meanwhile, considering the two-stage operation of power to gas (P2G), an active scheduling model for multi-energy coupled IES is established, with the optimization goal of minimizing the total cost. The results show that the average absolute error and root mean square error of the proposed prediction model are decreased by 1.44% and 3.94%, respectively, while the fitting coefficient is improved by 1.18%. After adopting green certificate-stepped carbon joint trading and coupling with two-stage power-to-gas equipment, the total carbon emissions and the scheduling cost of the IES are decreased by 13.95% and 9.27%, respectively, compared to the single basic scenario.

黑龙江省省属本科高校基本科研业务费项目（2024-KYYWF-1036）；黑龙江科技大学引进高层次人才科研启动基金项目（HKDQDJ202514）