Optimization of large-scale Direct Air Capture (DAC) Model using SCR algorithm

This paper describes optimization studies of a large-scale fixed bed reactor model using Aspen Adsorption cycle simulations. The model uses Lewatit® VP OC 1065 amine-functionalized adsorbents and temperature vacuum swing adsorption (TVSA) cycles to capture CO2 from the ambient air. Building a comprehensive direct air capture (DAC) model to optimize process design and cost is crucial to assess the feasibility of DAC technologies and therefore, a novel surrogate-based derivative free global optimization algorithm, referred to as SCR is implemented to evaluate a large-scale DAC system. Lastly, in order to achieve zero emissions and assess the viability of deploying large-scale DAC systems, assessments involving emission factors of various energy sources in different countries’ electricity energy grid systems are studied. The optimization study showed a reduction in capture cost by 45% compared to the base case.