A rapid multi-objective optimization of pressure and temperature swing adsorption for CO2 capture based on simplified equilibrium model

Abstract

• A new equilibrium model for PTSA cycle is developed for rapid optimization. • The equilibrium model is verified by 2-D dynamic model. • The equilibrium model is used to optimize the cycle rapidly and screen adsorbents. • Zeolite 13X-APG has the best exergy efficiency among twenty adsorbents. • The error of the equilibrium model is controlled to 0.1% by correction. CO 2 capture by adsorption is considered to be one of the powerful technologies to achieve carbon neutrality and alleviate global warming. However, adsorption technology is still limited by cycle performance such as energy cost, etc. at the present stage, and the optimization research of the technology deserves attention. But the development of optimization technology is limited by the large time of experiment and large calculation cost and simulation. In recent years, computational model based on equilibrium hypothesis has been used in rapid cycle optimization because of its relatively accurate calculation results and less computation. In this paper, a new equilibrium model was developed for a four-step pressure and temperature swing adsorption (PTSA) cycle for CO 2 capture, and it was verified by a complex model, i.e., 2-D dynamic model. Then, the parameters of PTSA cycle were optimized by using equilibrium model, and the relationship of cycle performance (purity, recovery and exergy efficiency) was analyzed. It is found that the number of optimal Pareto solutions is the largest when the adsorption temperature is 293 K (ambient temperature). There is a competitive relationship between recovery rate and exergy efficiency. Twenty adsorbents were screened according to their optimal circulation indexes, and Zeolite 13X-APG (ZEO_13X_APG) has the best exergy efficiency among them. Finally, a method to improve the optimization accuracy by correction was introduced, and the error of cycle performance was reduced to 0.1%.