Simulation and Multi-Objective Optimization of a Trickle-Bed Reactor for Diesel Hydrotreating by a Heterogeneous Model Using Non-Dominated Sorting Genetic Algorithm II

Hydrotreating processes for diesel fuels are becoming increasingly important, owing to environmental regulations limiting sulfur and aromatic compounds, which are becoming more strict. Among investigations into hydrotreating modeling, most of the studies use a homogeneous model to simulate the reactor. However, for a real industrial reactor, that is not always an accurate assumption. Furthermore, reports of efforts to find the best operating conditions are very scarce. In this study, a heterogeneous model of three main reactions-hydro-desulfurization, hydro-denitrogenation, and hydro-dearomatization was applied to simulate the hydrotreating reactor. The model results show a good agreement with literature experimental data. The effects of important operational parameters such as temperature, pressure, liquid hourly space velocity, and H-2/oil ratio on various hydrotreating reactions are also evaluated. Finally, a multi-objective optimization based on non-dominated sorting genetic algorithm II is carried out to find the best operating conditions for a diesel fuel hydrotreating reactor.