(391f) Multiobjective Optimization in the Design of a Process for Hydrodesulfurization of Diesel

The hydrodesulfurization (HDS) process is widely used to remove sulfur found in diesel. Conventional HDS processes basically consist of a reaction system where the organic sulfur compounds react with hydrogen to obtain organic compounds and hydrogen sulfide besides a separation system to remove compounds of diesel and a recirculation system. A technological alternative improvement for this process is the reactive distillation, which allows to perform the HDS operation and separation of products in a single unit process involving a considerable energy saving and cost investment. The distillation reactor-side (DSRC) also has been proposed to remove sulfur compounds of diesel. The design and optimization of a HDS process involves the selection of the configuration and the operating conditions to minimize the total annual cost, CO₂ emissions and the amount of sulfur compounds. In general, the optimal design of HDS process is a highly non-linear and multivariable problem, with the presence of both continuous and discontinuous design variables. In addition, the objective function used as optimization criterion is generally non-convex with several local optimums and subject to several constraints. The use of stochastic optimizers, which deals with multi-modal and non-convex problems, can be an effective way to face the challenging characteristics involved in the design of distillation columns. Stochastic global optimization algorithms are capable of solving, robustly and efficiently, the challenging multi-modal optimization problem, and they appear to be a suitable alternative for the design and optimization of complex separation schemes. In this work, we have implemented a stochastic global optimization method to obtain the design and optimization of three distillation reactor-side (DSRC) in the HDS process. In particular, we have used a multiobjective optimization based on differential evolution with tabu list coupled to Aspen ONE Aspen Plus. The results obtained in the Pareto Fronts indicate competition between total annual cost, CO₂ emissions and the amount of sulfur compounds of the HDS process. These results are useful to identify trends in the operational conditions in the DSRC process.