Master Thesis : Development of short-cut cost correlations for CO2 capture technologies using data driven approaches: the case of the hot potassium carbonate process (including an introduction to research methodology)

Abstract

Post-combustion CO₂ capture by chemical absorption is the most mature and readily retrofittable route for decarbonising the existing industrial and power fleet, yet rapid economic screening across diverse CO₂ sources remains hampered by the need for case-by-case process simulation. While shortcut cost correlations exist for monoethanolamine (MEA) capture, none have been published for the unpromoted hot potassium carbonate (K₂CO₃) process, whose elevated-pressure operating regime remains largely unexplored. This thesis develops and validates the first shortcut cost correlation framework for unpromoted aqueous K₂CO₃ post-combustion capture. A rate-based Aspen Plus model employing the electrolyte non-random two-liquid (eNRTL) framework was used to perform a systematic CAPEX–OPEX optimisation over a a 20-point parametric grid spanning inlet CO₂ concentrations of 5 to 50 mol% and capture scales of 135 to 1500 kt CO₂/year with an absorber pressure between 4-50 bar. The optimal pressure, absorber height, and stripper height were identified at each point by minimising the total annualised cost per tonne of CO₂. From the resulting cost-optimised dataset, correlations were fitted expressing total equipment cost and specific utility consumption as explicit functions of CO₂ inlet concentration and flue gas molar flow rate, deliberately decoupled from final cost assembly so users can apply their own cost methodology and utility prices. The optimum capture cost falls roughly two-fold per step increase in concentration, from about 378 €/tCO₂ at 5 mol% to 65 €/tCO₂ at 50 mol% at the 1078 kt/year reference scale. The framework enables rapid economic screening of K₂CO₃ capture across a wide range of industrial CO₂ sources, while confirming that unpromoted K₂CO₃ remains comparable with MEA only at high inlet concentrations, motivating promoted formulations as future work.