Carbon Dioxide Capture by Chemical Absorption: Energy Optimization and Analysis of Dynamic Viscosity of Solvents

Abstract

Global warming resulted from the emissions of greenhouse gases; especially carbon dioxide has received widespread attention. The concentration of CO2 in the atmosphere reaches 400 ppmv and that is a considerably high value for emission's regulations. Efficient CO2 mitigation techniques will become increasingly demanding due to environmental issues. There are many sources that release CO2 and combustion of fossil fuel plays the major role. Coal fired power plants are the most prominent CO2 emitting source today. Though with various carbon mitigation technologies available, there are still challenges remain unsolved. One of the most promising technologies for carbon mitigation is the chemical absorption process based on post combustion. The operation of the chemical absorption process is deeply reviewed for the present study.

The CO2 capture model was developed in Aspen Plus process simulation software. The available parameters in the Aspen Plus databank and the data available in the literatures are used for the development of the model. There are four different types of case studies which are taken into consideration, they are flue gases from coal fired power plant, gas fired power plant, cement industry and aluminium industry as CO2 emitting manmade sources.

The main drawback of the chemical absorption process is a high amount of re-generation energy requirement in stripper. Therefore, main attention was focused on re-boiler energy minimization with several optimization steps. The major concerns of this technology, including removal efficiency optimization and re-boiler energy minimization, are addressed by implementing solvent condition, solvent flow rate, parameter optimization, and selection of packing material. More effective and less energy consuming solvent and the parameter values of selected solvents are identified for model implementation.

The simulations of the absorption process are presented for sensitivity analyses of important parameters on the removal efficiency: lean loading, solvent concentration, flue gas temperature, the solvent temperature, packing height, packing diameter and absorber pressure. Moreover, the sensitivity analysis was performed for single parameter effect, as well as, multiple parameters effect on the desired output. Both the main effect and interaction effect of the parameters have been studied. The data collected from simulation are analyzed using Principal Component Analysis (PCA), Principal Component Regression (PCR) and Partial Least Square-regression (PLS-R) to develop the linear relationship between parameters and output. The most important parameters (highest influence parameters on re-boiler duty) are lean CO2 loading, absorber diameter and absorber height. Similarly, the correlation between variables were studied for CO2 removal efficiency, which indicates that inlet solvent flow rate, absorber packing height and diameter, absorber pressure and temperature of the solvent stream are positively correlated with CO2 removal efficiency whereas the lean loading and temperature of flue gas are negatively correlated with efficiency.

The required re-boiler energy demand was calculated for four different cases with optimized parameter values for every section in the process. The lean solvent loading and solvent concentration, were found to have a major effect on the solvent circulation and then on the re-generation energy in stripping section, which has been identified as the main problem for implementing carbon capture plant in real industry. Even though, increasing the amine concentration will cause corrosion effects that can be minimized by adding a small amount of inhibitors. Use of blended amines to replace the single amines also gives a significant impact on re-generation energy.

The implemented model is designed for the flue gases from coal fired power plant, gas fired power plant, cement plant as well as the aluminium industry. The required re-boiler duty was calculated for every situation. The temperature profiles, as well as CO2 loading profiles, were analyzed to check the process behavior.

Moreover, physical properties of the solvents are also important to model the carbon capture process. However, lack of data availability for the physical properties of amines was motivated to perform the experimental studies, as well. The dynamic viscosity of the amine solutions was identified as one of the main physical properties which are needed for implementing the process design. Different amines such as, monoethanolamine (MEA), diethanolamine (DEA), N-methyldiethanolamine (MDEA) were mainly considered for the laboratory experiments. Viscosity experiments were performed for single amines as well as blended amines (blend of two amines). Amine concentration was varied from (10-100) % mass basis with the temperature variation from (293.15- 423.15) K. The amine solutions were analyzed for the CO2 loaded as well as unloaded solutions. Amine viscosities with CO2 loading are rare can be found in literatures and it was only available for low temperature values. Eventually, measured viscosity data were analyzed with the values available in the literature to validate the experimental results. Moreover, available linear regression models were used to fit the data into the correlations. The measured viscosities are in good agreement with the literature data.