Simulation-Based Optimization of a Multiple Gas Feed Sweetening Process

For an energy-intensive
sweetening process, it is common that sour
gases from different sources are sent to a single sweetening plant
in industries. In our previous work, a multiple gas feed sweetening
process was proposed, which can simultaneously improve the purity
of H2S and reduce the energy consumption of the plant.
This study aims to develop the superstructure of that process and
use a simulation-based optimization framework with Aspen HYSYS as
the process simulator and particle swarm optimization algorithm as
the optimizer. In addition, by taking full advantage of the robustness
of the built-in algorithm of the simulator, the convergence of the
model is improved; meanwhile, simplification of the process and reduction
of the optimization time are accessible with the proposed design specifications
and assumptions. For a convergence-difficult column, a stepwise convergence
adjustment was used to ensure their convergence. Based on this, the
robustness and effectiveness of the method is proven through a case
study, and it can also provide guidance for model selection, process
simplification, and optimization of the same type of absorption process.