Two-Stage Robust Optimization for Integrated Energy Systems With Bidirectional Demand Response and Tiered Carbon Trading

Abstract Amid accelerating energy transition and carbon reduction goals, integrated energy systems offer multi-energy complementary to enhance efficiency and reduce carbon emissions. This article develops a park-level integrated energy systems model incorporating wind power, combined heat and power, carbon capture, and power to gas, proposing a two-stage robust scheduling method integrating a tiered carbon trading mechanism and bidirectional demand response. Adjustable uncertainty sets characterize renewable and load fluctuations, with the column and constraint generation algorithm ensures tractable optimization. Case studies demonstrate that the tiered carbon pricing mechanism reduces carbon emissions by 50.40% (from 44,052.73 kg to 21,827.00 kg) and carbon costs by 5.40%. The demand response mechanism with energy storage reduces the electricity load peak–valley difference by 150 kW and electricity purchase costs by 4.60%, effectively improving flexibility and system balance. Although total operating cost rises slightly by 5.84% compared to deterministic optimization, the robustness and operational safety of scheduling are significantly enhanced. The proposed methods promote the coordinated operation of the electricity-carbon system, optimizing economic dispatch, and address uncertainties.