Economic Analysis of CO2 DEA-MDEA Removal System

Removal of CO2 using aqueous amine systems is one of the popular methods in treating flue gas. Aqueous amines are organic solvents that selectively remove CO2 gas from waste stream. Various types of amines are often used together in a blend of mixture to maximize their advantages. This paper aims to conduct a sensitivity analysis on how changes in the market price of one type of amine in an amine mixture will affect the overall cost of flue gas treatment. It is an extension of the work done by Rodrigues (2011), who optimized the post-combustion CO2 capture using an amine mixture consisting of Methyldiethanolamine (MDEA) and Diethanolamine (DEA). Rodriguez has successfully determined the mass fraction of the MDEA-DEA in an amine mixture that will achieve a CO2 removal target with minimal cost. In this paper, 95% removal target data will be used as a basis. This paper further Rodriguez’s work by adding the dimension of sensitivity analysis to the cost optimization. The market price of the 2 amine solvents is expressed as a price ratio to yield a single value to work with. The investigation is carried out using HYSIS simulation software, in which the fluid package Amine Property Package is used with Li-Mather as the model. A simplified process flow sheet of the CO2 amine system is simulated which involve two major equipment: the absorber and regenerator. The simulation shows the minimum solvent flow rate to achieve the 95% CO2 removal target, amount of flue gas removed by the solvent, and the energy of regeneration of the recycled solvent. In addition to that, by using the initial cost function described by Rodriguez (2011), several other models of the minimum cost function that incorporated the MDEA-DEA price ratio can be created and the sensitivity analysis for each model can be investigated. The most feasible model to describe how the changes in market price will affect the minimum cost is selected. The result shows that an economic analysis with much useful information can be interpreted from the selected cost function.