Optimal Dispatch of Power System Considering Low Carbon Demand Response of Electric Vehicles

Abstract

This research suggests a double-layer optimization operation approach that considers electric vehicle participation when low-carbon scheduling is used within the power system; there is a need to provide assistance in the transition to low-carbon energy sources. The Monte Carlo technique is used to simulate data for electric vehicle load predictions. The top model uses the grid operators as its central organization. It sets the lowest generation and carbon trading costs as its objective, engages directly in the carbon trading market, determines the ideal model for unit output distribution, and determines each unit's actual production. In the lower model, the operators of the electric vehicle cluster sense changes in the upper carbon emission factor signal, modify their charging behavior through demand response, calculate the single-day reduction of carbon emissions, and the attainment of the benefits associated with the mitigation of carbon exhausts. A carbon emissions model is used to assign the responsibility for carbon exhausts from the user side of the generator unit to the carbon discharge aspect mechanism. Four distinct scenarios are built up, illustrating the enhanced IEEE 14 node system, to examine and confirm the efficacy of the suggested optimum scheduling model.