Construction of a shortcut model for amine-based $CO_2$ capture process

Abstract

A carbon dioxide capture process provides an alternative option that avoids $CO_2$ emission while consuming fossil fuels. The major obstacle for application of this $CO_2$ capture process in industry comes from high $CO_2$ capture cost, and it is essential to estimate capture cost for each stationary flue gases. A well-constructed shortcut model allows to estimate the capture cost for the $CO_2$ capture process without time-consuming rigorous process simulation. This thesis dissertation proposes a methodological framework to construct a shortcut model for a specific $CO_2$ capture process. As examples, shortcut models for monoethanolamine (MEA) and piperazine (PZ) based $CO_2$ capture process are constructed. The procedure for shortcut model construction includes process model validation, rigorous process simulation with optimization, and techno-economic evaluation. Dataset that represents wide range of flue gases and corresponding optimized $CO_2$ capture process models are generated and fitted to construct the shortcut models. Hopefully, not only can the methodology be applied to amine scrubbing with various amines and their blends, but also other $CO_2$ capture technologies such as membrane separation and adsorptions. In addition, the constructed shortcut models can be incorporated into a carbon-capture-utilization-sequestration (CCUS) superstructure network. Then, the superstructure network are optimized and optimal CCUS pathway is identified by means of more accurate non-linear programming.