Abstract: Against the dual backdrop of steadily advancing the "dual carbon" goals and increasing operational uncertainties in integrated energy systems (IES), achieving low-carbon and robust scheduling has become a critical challenge. To address the low-carbon scheduling problem under wind power and load fluctuations, this paper developed a coordinated optimization model that integrates Oxy-fuel combustion carbon capture (OXYCC), hydrogen blending and reward-penalty tiered carbon trading mechanism, and a two-stage robust optimization approach was introduced to enhance the system’s scheduling feasibility and operational stability under uncertainties. The column-and-constraint generation (C&CG) algorithm was employed to improve the model’s computational efficiency. Simulation results show that the proposed model achieves a 29.99% reduction in carbon emissions and a 16.11% decrease in system operational costs, and also maintains strong performance under multi-source fluctuations and disturbances, which verifies its effectiveness and practical applicability in addressing dual objectives of low-carbon operation and robust scheduling.