Modeling, Simulation, and Multi-Objective Optimization of Moving Bed Radial Flow Dehydrogenation Reactors

The main object of this research, is modeling and multi-objective optimization of radial flow moving bed reactors to produce propylene through propane dehydrogenation considering catalyst deactivation. The propane dehydrogenation process consists of four series catalytic reactors equipped with inter-stage heaters that the feed flows radially and the catalyst moves downward along the axial direction due to gravitational force. In the first step, the dehydrogenation reactors are heterogeneously modeled based on the mass and energy conservation laws considering catalyst decay. To prove the accuracy of the developed model, the simulation results are compared with the plant data. In the next step, the optimal operating condition of the process is obtained considering propane conversion and propylene selectivity as objective functions. In this regard, a multi-objective optimization problem is formulated and the optimal Pareto front is developed by non-sporting genetic algorithm II. Then, a single optimal solution is selected from the list of alternatives in the Pareto front curve by one of the decision-making methods. The results showed that applying the obtained optimal condition to the system improves propylene production capacity by about 3.12 %.