The catalytic synthesis of methanol from hydrogen and carbon dioxide is the key to solving the technical problem of "production, storage, transportation, addition, and utilization" of hydrogen energy. This study highlights a mathematical model of generalized energy storage for methanol synthesis. It focuses on the design of a layered optimization and control scheme for a virtual power plant, focusing on source-network load-storage. The upper layer of the plant encompasses that of generalized energy storage for use with wind power and photovoltaics proposed, which can track several factors. Such factors are generation scheduling, the introduction of virtual power plants to consumers of the master-slave game theory, the use of genetic algorithms to hone the price of electricity at different times of the day, and responses to user demands, thus reducing the net load peak and valley differences. The lower layer is comprised of external power trading as the ultimate guarantee. This shall be combined with generalized energy storage to achieve balance between power supply and power demand, especially the Sinh Cosh optimization algorithm, to enhance the source storage and ensure that the virtual power plant operates under low carbon conditions. Finally, compared to different schemes, the proposed scheme can effectively increase the level of renewable energy consumption and promote regional decarbonization. Also, the proposed scheme can improve the comprehensive operational efficiency of virtual power plants.