A Surrogate-Assisted Approach for the Optimal Synthesis of Refinery Hydrogen Networks

This
paper presents a surrogate-assisted methodology for the optimal
synthesis of refinery hydrogen networks, which fully considers the
impact of vapor–liquid equilibrium in the flash separation
unit, to study the interactions between the varying K-values and the optimal configuration of the overall hydrogen network.
In addition, the formations of light hydrocarbons and hydrogen sulfide
in the hydroprocessing reactors are calculated by the proposed method.
To deliver a more accurate and efficient modeling and optimization,
high dimensional model representation (HDMR) is applied to approximate
the first-principle-based models of the hydroprocessing reactor and
flash separation unit. The established surrogate models are integrated
with other realistic system constraints, thus formulating a nonlinear
programming model for the optimization of refinery hydrogen networks.
The approach is illustrated by its application to a case study, in
which the results demonstrate that it yields significant differences
in the component concentrations of the reactor inlet streams compared
to the previous study. The differences further lead to different configurations
of the optimal hydrogen network. Therefore, one can conclude that
the proposed method can deliver more accurate and realistic results.