A novel standpoint of Pressure Swing Adsorption processes multi-objective optimization: An approach based on feasible operation region mapping

Abstract

Optimization of cyclic adsorption processes is a challenging issue due to the dynamic-operating complexity of these processes. In this context, this work proposes a new approach for multi-objective optimization of Pressure Swing Adsorption (PSA) units, extending the concept of the Pareto front to Pareto region. The proposed methodology, hitherto unexplored in the literature, consists of integrating a likelihood test, an arrangement from the Fisher–Snedecor test to the solution of a multi-objective problem provided by a Swarm Particle Optimization technique. The Pareto region is divided into operating sub-regions that meet the optimization constraints and prioritize a determined objective by a clustering process. These sub-regions make the operation more flexible. Furthermore, the analysis of the operating variables feasible operation interval demonstrated to be an important tool to provide information regarding the system behavior. As a study case, it is presented the optimization of a PSA process for syngas purification. The results demonstrate that the methodology proposed here uses the feasible operation region map and the clustering strategy to exploit the multi-objective optimization. Therefore, providing a more reliable and precise optimization of PSA units, while providing an important tool for making decisions in the PSA system.