A Low-Carbon Robust Optimization Scheduling Model for Microgrids Considering Electric Vehicles

To enhance the stability, economic efficiency of microgrids systems and reduce its carbon emission, this paper proposes a two-stage low-carbon robust optimization scheduling model considering electric vehicles (EVs), the uncertainties of distributed generation and load of microgrids. The model optimizes the dispatching scheme with the lowest operating cost under the worst-case scenario, along with detailed analyze the operational cost of microgrids under different charging modes of EVs and the impact of carbon trading mechanisms. The experimental results indicate that compared to unregulated charging, the operating cost decreases by 7.6% with smart charging and discharging. Furthermore, with the incorporation of carbon trading mechanism, microgrid carbon emissions reduce by 54.2%, while the operating cost increases by only 1.4%. These results validate the efficacy of the model.