Cost-effective process design for methanol synthesis from carbon dioxide hydrogenation

This study explores the development and optimization of the methanol synthesis process via carbon dioxide hydrogenation. To improve the feasibility of products produced from CO₂ and enhance CO₂ utilization, thereby reducing environmental impact, a cost-effective process must be developed. Accordingly, this research introduces an optimization framework capable of handling diverse process configurations, operating variables, and their interactions. This approach enables effective optimization using total annual cost (TAC) as the objective function and significantly enhances process design efficiency. The framework integrates Aspen Plus® with a genetic algorithm (GA) in the MATLAB® environment, allowing automated solution searches and the identification of optimal designs through an elimination-based mechanism. A case study demonstrates that the optimization process refines the process configuration and operating conditions, resulting in significant reductions in operating and capital costs. The optimized process achieves a 44.9 % cost reduction compared to the reference case, highlighting its economic potential. This advancement strengthens the competitiveness of methanol synthesis and promotes broader adoption of CO₂ utilization technologies in industrial applications.