Pressure Swing Adsorption (PSA) is an efficient method for gas separation, and is a potential candidate for carbon dioxide (CO2) capture from power plants. However, few PSA cycles have been designed for this purpose and the optimization of PSA systems for CO2 capture remains a very challenging task. In this study, we present a systematic optimization-based formulation for the synthesis and design of novel PSA cycles for CO2 capture in an IGCC flowsheet, which can simultaneously produce hydrogen (H2) and CO2 at a high purity. Here, we apply a superstructure-based approach to simultaneously determine optimal cycle configurations and design parameters for PSA units. This approach integrates automatic differentiation, efficient ODE solvers for the state and sensitivity equations of the PSA model and state of the art NLP solvers. Three optimization formulations are proposed and two PSA case studies are considered. The first case study considers a binary separation of H2 and CO2 at high purity, where specific energy is minimized, while the second considers a larger five component separation.
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