Direct Air Capture (DAC) processes have recently gained a lot of interest, as they could play a major role in achieving carbon neutrality. The carbon dioxide that is obtained from such processes, can be used in power-to-gas and power-to-liquid applications such as the generation of methane or methanol and help to reduce the use of fossil fuel within the chemical industry. Many studies also suggest that it will be necessary to remove carbon dioxide from the atmosphere to reduce the effects of climate change. Different technologies exist to enable carbon capture, most of them including ad- and absorption processes. At TLK Energy, we model this kind of systems in Modelica using our TIL Adsorption Add-On or our Process Systems Library.
The goal of this thesis is to create a dynamic model of a DAC system and optimize it. The model will be set-up in Modelica using the libraries mentioned previously. Once it is modelled, the DAC system will be evaluated for various weather conditions and locations using numerical optimization. To enable this optimization, the simulation needs to be fast and robust. The results will then be compared to those obtained in a previous thesis for another type of DAC process.
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