With the advancement of the global energy transition, reducing carbon emissions and improving energy utilization efficiency have become important objectives in power⁃system optimization.As a new form of power scheduling and management, a microgrid uses distributed energy resources and intelligent dispatching technologies to achieve the optimal allocation and scheduling of energy.An improved non⁃dominated sorting genetic algorithm is proposed,and an optimal scheduling model for a microgrid integrating carbon capture and hydrogen energy storage is established. For the non⁃dominated sorting genetic algorithm Ⅱ (NSGA⁃Ⅱ), the original initial population and parent⁃selection strategy are replaced by a good⁃point⁃set population and linear⁃ranking parent selection. Generational distance is used to quantify the convergence performance before and after algorithm improvement. The contributions of carbon capture and hydrogen energy storage to emission reduction and economic performance are verified, and the levels of curtailed power and convergence performance before and after algorithm improvement are comparatively analyzed. The results show that the improved NSGA⁃Ⅱ algorithm has better convergence and global search capability. A microgrid combining carbon capture with hydrogen storage and hydrogen sales can effectively improve both economic performance and emission⁃reduction capability while satisfying load accommodation requirements, and its convergence is significantly better than that of the original method.