Low-carbon integrated energy system scheduling considering electric vehicle demand response

Under the dual-carbon context, integrating electric vehicles (EVs) into the power grid faces numerous challenges. This paper proposes an electric vehicle demand response (EVDR) mechanism and applies it to a nonlinear integrated energy system (IES) to address carbon emissions and energy efficiency issues. To further reduce carbon emissions, the model incorporates carbon capture technology and carbon penalty mechanisms. The model is transformed into a mixed-integer linear programming (MILP) problem through piecewise linearization and solved using CPLEX. Experimental results show that the integrated energy scheduling model achieves load balancing through flexible EV charging scheduling, increases carbon emission costs by 1.5%, reduces total costs by 2.55%, and significantly enhances system flexibility. Additionally, the model effectively utilizes renewable energy, with zero curtailment costs for wind and photovoltaic power, reducing reliance on traditional energy sources and minimizing waste of renewable energy. The carbon capture system significantly lowers both carbon emission costs and total costs; increasing the capture rate limit by 20% can reduce total costs by 24.29%, enhancing the system's environmental friendliness. The introduction of carbon penalty mechanisms encourages system operators to adopt more environmentally friendly production methods, promoting the transition of energy systems towards low-carbon development. The proposed scheduling model has significant theoretical and practical implications for the intelligent management of future energy systems and the progress towards carbon neutrality.