Optimization Scheduling Strategy for Microgrid Considering Carbon Emission Costs

To address the issue of elevated carbon emissions in microgrids dominated by renewable energy sources, stemming from excessive photovoltaic curtailment and the frequent cycling of diesel generators, this study develops an energy optimization scheduling model. This model prioritizes operational expenses and carbon emission costs as dual objectives for microgrids with a significant share of renewable energy. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is utilized to resolve the model effectively. The findings indicate that integrating carbon emission optimization into the objective function framework significantly enhances the microgrid’s scheduling performance and bolsters the efficiency of renewable energy utilization.