Simulation and optimization of methanol production process via bi-reforming of methane: A novel genetic algorithm-based approach in Python

• Published in: International journal of hydrogen energy Vol. 101; pp. 1161 - 1171
• Main Authors: Rouhandeh, Hossein, Behroozsarand, Alireza
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 03.02.2025
• Subjects: Bi-reforming of methane; Carbon dioxide utilization; Genetic algorithm; Methanol production; Python programming; Python programming; Bi-reforming of methane; Carbon dioxide utilization; Genetic algorithm; Methanol production
• ISSN: 0360-3199
• DOI: 10.1016/j.ijhydene.2025.01.003

Bi-reforming of methane (BRM) is a promising method for syngas production in Methanol synthesis that consumes CH4 and CO2 while allowing feed ratio tuning. In this study as main novelty, an innovative optimization approach(integratrd genetic algorithm, Python programming language, and Aspen Plus software) for Methanol synthesis using a bi-reforming process to increase productivity and reduce CO2 emissions is proposed. Furthermore, By using a genetic algorithm, Python programming language, and integrated Aspen Plus software, the optimal temperature and pressure feed conditions were determined for a BRM reactor. The molar feed ratio of CH4: CO2:H2O = 1:0.36:0.9 at a temperature of 901 °C and a pressure of 5 bar, instead of 3:1:2 and 1:1:2, was recognized as the optimal ratio in the bi-reforming process. The optimal conditions resulted in 93% CH4 conversion, 76% CO2 conversion, and an H2/CO ratio of 2.08, achieving the ideal stoichiometric number (M = 2) for Methanol synthesis. Comparative analysis with a referenced method showed that the proposed process produces an additional 11.8 tonne/h of methanol, consumes 7.63 tonne/h more CO2, and reduces steam consumption by 54.11 tonne/h. Moreover, the process exhibits improved environmental performance, consuming over 20% more CO2.These results indicate that the BRM process can be a suitable alternative to the SMR process in methanol synthesis. [Display omitted] •Integration of GA, Python programming, and Aspen Plus has been applied in the Methanol process.•Comparison of Proposed with referenced method showed increasing 11.8 tonne/h methanol productivity.•Proposed process consumes 7.63 tonne/h more CO2 and reduces 54.11 tonne/h steam consumption.•The optimal conditions found CH4:CO2:H2O molar ratio of 1:0.36:0.9 at 901 °C and 5 bar pressure.