Power-to-methanol process assessment using enhanced kinetic models

In the energy transition scenario, Power-to-X processes play a crucial role by converting surplus electricity from renewable sources into fuels, chemicals, and other energy carriers. These technologies not only help to balance the supply and demand of energy but also promote decarbonization. In this study, the conversion of carbon dioxide and hydrogen into methanol (Power-to-Methanol) as a strategic solution to store and transport hydrogen was evaluated by modeling and simulation. The investigation addressed the rate laws governing the reactions in the hydrogenation of pollutant gases into methanol. Refitted and original Bussche-Froment (BF) and Graaf kinetic models were used to understand and identify the key factors in process efficiency for improving competitiveness compared to conventional processes. The sensitivity analysis revealed some similarities in both models; however, discrepancies in conversion predictions reached up to 49%, particularly at intermediate residence times, low temperatures, and high pressures. Selecting an appropriate residence time (below 0.1 h) proved critical to reducing divergences between models, providing actionable insight for reliable process design and optimization. These discrepancies between the models contribute to a broad theoretical optimal operating window for the process. Considering both models, the methanol production and CO 2 conversions were higher in temperatures between 200 and 250 °C. In this optimal temperature range, increasing the pressure contributed to higher methanol production. Increasing H 2 /CO 2 ratio favored CO 2 conversion, achieving an average for both models of 44% with a ratio of 8:1. However, a ratio of 3:1 for the Graaf model and 2:1 for the BF model resulted in maximum methanol production. Finally, increasing the CO concentration raised the obtained methanol concentration but resulted in lower carbon dioxide conversion. • Critical 'reliability window' identified for methanol reactor design. • Model divergences of up to 49% observed at high pressures and low temperatures. • Operating at residence times below 0.1 h ensures kinetic model convergence. • Kinetic model divergences for Power-to-Methanol were quantified.