Optimization of Al-Doura Catalytic Naphtha Reforming Process Using Genetic Algorithm


Optimization of Al-Doura catalytic naphtha reforming process was done using genetic algorithm. The objective of optimization is maximization yield of the aromatics in order to increase the octane number of reformate. One-dimensional steady-state mathematical model was made to study the effect of feedstock composition, feed temperature, total pressure and hydrogen to hydrocarbon feed ratio on the reformate compositions. Detailed kinetic model was developed to describe the reaction kinetic, the model involving 29 components, 1 to 11 carbon atoms for n-paraffins, 5 to 10 carbon atoms for iso-paraffins and 6 to 11 carbon atom for naphthenes and aromatics with 83 reactions. Using Genetic Algorithm, 186 parameters of the proposed kinetic model were predicted depending on plant results collected over two months from Al-Doura reforming process which located in the south of Baghdad. The validity of the kinetic model was approved by comparing the results of developed kinetic model with the actual process results. Genetic algorithm was used again to optimize the commercial reforming process depending on reformate compositions. Optimization was carried out in temperature range between 450 to 520°C; total pressure range 5 to 35 bar; hydrogen to hydrocarbon ratio 3 to 8 and by varying the percentage of catalyst for each one of four reactors. Optimization results shows that, it’s possible to increase the aromatics composition in reformate from 63.42 % in actual unit to 70.89 % by changing the design variables and operating conditions.