Automated process synthesis for optimal flowsheet design of a hybrid membrane cryogenic carbon capture process

Process flowsheet synthesis is one critical step in the design of any chemical process and is a key factor for consideration in plant operation and economic efficiencies. Previously an automated process flowsheet synthesis is outlined that using a systematic computational approach. This method considers the design and operation variables to converge to an optimum flowsheet using genetic algorithm (GA). In this study, this algorithm is implemented to investigate the potential for a hybrid process combining membrane and cryogenic separation to achieve an efficient and effective carbon dioxide (CO2) capture plant design. The optimum flowsheet is selected using an objective function by screening among a variety of random flowsheets. The studied objective function is a combination of three effective factors in the performance of a flowsheet for this process which are: permeate CO2 purity, CO2 recovery of the system, and energy penalty of the configuration. The outcome of the optimization algorithm is presented as a structurally and parametrically optimized process flowsheet. Within the defined constraints the algorithm estimates that the optimum configuration of a hybrid structure of the membrane/cryogenic system for a three membrane unit process can provide CO2 permeate purity of 0.941, CO2 recovery of 0.979 and energy penalty of 1.249 GJ/t. While the same values for a membrane-based CO2 capture system are 0.940, 0.865 and 3.722 for the optimum estimated flowsheet. The presented results for the optimum hybrid process in comparison with other options shows a promising possibility of exchanging conventional technologies with the proposed optimal configuration. These results along with a global optimality analysis demonstrate the value of automated process synthesis in developing optimal process flowsheet designs.