Direct air capture; process modelling; surrogate-based optimization; TVSA; Chemical Engineering (all); Computer Science Applications
Abstract :
[en] 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.
Disciplines :
Chemical engineering
Author, co-author :
Kim, So-Mang ; Université de Liège - ULiège > Chemical engineering
Zaryab, Syed Ali; Politecnico di Milano, Department of Energy, Milan, Italy
Fakhraddinfakhriazar, Salar ; Université de Liège - ULiège > Department of Chemical Engineering > PEPs - Products, Environment, and Processes
Martelli, Emanuele; Politecnico di Milano, Department of Energy, Milan, Italy
Léonard, Grégoire ; Université de Liège - ULiège > Department of Chemical Engineering > PEPs - Products, Environment, and Processes
Language :
English
Title :
Optimization of large-scale Direct Air Capture (DAC) Model using SCR algorithm
Publication date :
2023
Event name :
33rd European Symposium on Computer Aided Process Engineering (ESCAPE33)
The authors are grateful to the Belgian Federal Public Service Economy and to the Belgian Energy Transition Fund which support this research within the project PROCURA.
