Tri-stage Optimal Scheduling for Microgrid Cluster Considering Carbon Emissions

This study presents a method for optimizing the scheduling of microgrid clusters by comprehensively considering carbon emission factors. Initially, we formulate a mathematical model for a single microgrid, encompassing diverse energy sources such as wind turbines (WT), photovoltaics (PV), fuel cells (FC), and controllable distributed generators (CDG). Subsequently, this model is extended to address microgrid clusters, with a specific focus on coordinating energy dispatch among subgrids. To enhance the scheduling optimization efficiency, a three-stage optimization strategy is introduced, involving rolling adjustments implemented through Model Predictive Control (MPC). Additionally, we integrate carbon emission costs and constraints into the objective function to provide a comprehensive consideration of carbon emission factors. The simulation results unequivocally demonstrate the substantial efficacy of this approach in enhancing the efficiency of microgrid cluster scheduling.