A molecular-level
kinetic model was constructed for a vacuum gas
oil hydroprocessing unit. The feedstock molecule selection was based
on typical arrangements of structural attributes in crude oil. Based
on the fundamental hydroprocessing chemistry, a reaction network was
developed for the feedstock molecules including 5747 reactions distributed
among 12 core types of reactions. The final molecular model contained
1532 unique species up to 45 carbons encompassing molecules up to
five aromatic rings with heteroatoms. To determine the initial condition
of the feedstock, a statistical approach was applied by using probability
density functions (PDFs) characterizing the molecules in terms of
their structural attributes. Experimental feed measurements were used
to determine the values of the PDF parameters. A library containing
21 sets of PDF parameters representing the range of the feed measurements
was established and used to determine the starting point for optimization.
Simulated feed properties showed excellent agreement with experimental
values. For the kinetic model, the reactor system was divided into
a series of 19 pseudo plug flow reactors (PFRs), one for each catalyst
layer, interspersed with the appropriate quench streams. Each pseudo-PFR
was modeled using a side-by-side reaction and vapor–liquid
equilibrium approach. The activity of each type of catalyst and the
deactivation due to coking and metal deposition were included in the
simulation. Quantitative structure/reactivity correlations were used
to greatly reduce the number of parameters in the model. The parameters
were optimized using a simulated annealing algorithm so that the model
results corresponded to the measured reactor effluent. The optimized
model showed good agreement with the experimental measurements. To
simplify the day-to-day running of the kinetic model while still allowing
developers to change and study the model in more advanced applications,
a user-friendly application was developed.
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