Simulating and Optimizing Auto-Thermal Reforming of Methane to Synthesis Gas Using a Non-Dominated Sorting Genetic Algorithm II Method

摘要

Conventional synthesis gas production plants consist of a natural gas steam reforming to CO + 3H(2) on Ni catalysts in a furnace. An alternative method for highly endothermic steam reforming is auto-thermal reforming. In this work, synthesis gas production by auto-thermal reforming was simulated based on a heterogeneous and one-dimensional model in two cases. The first case was the auto-thermal reformer of Dias and Assaf's study. The present work was validated by the reported experimental results. The second case was the fixed-bed catalytic auto-thermal reactor operated at high pressure, which was suitable for methanol production and Fischer-Tropsch reactions (baseline case). Then, the effect of operating variables on the system behavior was studied. Finally, Pareto-optimal solutions were determined by non-dominated sorting genetic algorithm II. The objectives included obtaining a H-2/CO ratio of 2 in the produced synthesis gas and the maximum methane conversion. The adjustable parameters were the feed temperature, mass flux, and O-2/CH4 and H2O/CH4 ratios in the feed.