Simulating and Optimizing Auto Thermal Reforming of Methane to Synthesis Gas Using a Non Dominated Sorting Genetic Algorithm II Method
Conventional synthesis gas production plants consist of a natural gas steam reforming to CO 3H2 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 H2/CO ratio of 2 in the produced synthesis gas and the maximum methane conversion. The adjustable parameters were the feed temperature, mass flux, and O2/CH4 and H2O/CH4 ratios in the feed.