Electrochemically mediated amine regeneration and proton concentration modulation processes for flue gas CO2 capture: Comparison and artificial intelligence-based optimization

Abstract

Among different carbon capture and sequestration (CCS) systems, ones that are based on the electrochemical processes are at the center of attention. Developing a CCS system with a high energy efficiency can facilitate their applications. In this study, two electrochemical CO2 capture systems are optimized and compared from energy consumption perspective. The considered systems are electrochemically mediated amine regeneration (EMAR) and electrochemically proton concentration modulation (EPCM). Both systems are modeled using reactions equilibrium constants and species activity methods and then, based on the presented chemical model, their heat and electricity loads are calculated. The chemical and electrochemical models are validated by comparing the species concentrations and electrochemical cell’s potential with those of previous works. Also, a comprehensive parametric study is presented based on the design parameters, where the performances of the two systems are also compared. Additionally, the energy performances of the systems are modeled using artificial neural network (ANN) to the optimization intention. The obtained ANNs, as a multi-objective optimization function considering heat and electricity loads as objectives, are introduced to the genetic algorithm. Applying the genetic algorithm, both objectives are minimized simultaneously and illustrated in a Pareto front diagram. The results show that the EMAR system at different optimum states always exhibits lower heat and electricity loads than the EPCM system. In trade-off mode, consumption of electricity and heat load for the EMAR system are 38.8 kJ/mol CO2 and 79.2 kJ/mol CO2, respectively, while those of the EPCM system are respectively 45.58 kJ/mol CO2 and 200.3 kJ/mol CO2.