Multi-Objective Optimal Scheduling of Integrated Energy Systems Considering Tiered Carbon Trading and Load-Side Demand Response

This paper proposes a multi-objective optimal scheduling model for integrated energy systems (IESs) that incorporates a tiered carbon emissions trading mechanism and load-side demand response (LDR) to promote sustainability. First, a reward–penalty-based tiered carbon cost model is embedded within the IES scheduling framework, internalizing carbon constraints and providing differentiated carbon price signals for emission reduction. Second, a refined demand response model is introduced, categorizing electrical and thermal loads to enhance flexibility in system operation. The demand response strategy allows for temporal load shifting and load reduction, optimizing the overall energy management. Third, the augmented epsilon-constraint method (AUGMECON) is employed to minimize both total operating costs and carbon emissions. Scenario-based simulations are conducted to evaluate system performance under different configurations: the integrated carbon trading and LDR model, a carbon-trading-only approach, and a baseline scenario. The results show that the proposed model achieves the best performance, reducing operating costs by 13.6% and carbon emissions by 7.0% compared to the baseline. Additionally, the combined approach improves renewable energy utilization and reduces reliance on high-carbon energy sources, demonstrating the effectiveness of integrating carbon trading and demand response strategies for low-carbon and sustainable energy system management.