(519b) Optimization of CO2 Capture Process with Aqueous Amines – a Comparison of Two Simulation-Optimization Approaches

Aqueous amine is a solvent considered for CO₂ recovery from the flue gas of a refinery gas turbine by chemical absorption/desorption process [1]. The performance and the economics of this process depends on the choice of amine absorbent and its concentration, the number of stages in absorber and stripper columns, and the operating conditions.

In this work, we used two different simulation-based optimization approaches to minimize the CO₂ capture cost for post-combustion CO₂ removal. The first simulation-based optimization technique uses local search space to estimate an appropriate direction to reduce the objective function, i.e., response surface methodologies. The optimal solution obtained using response surface methodologies will generally be a local optimum. In the second optimization approach, the simulation was used to build a surrogate model, i.e., an artificial neural network (ANN), of the objective function over the whole decision space, and the optimization was performed using the surrogate model. Depending on the accuracy of the surrogate models, the solutions obtained using this approach can be shown to be global within the bounds of the data used to generate the surrogate models.

The impact of different amines absorbents, design parameters and operating conditions on the CO₂ capture cost were analyzed using both optimization techniques. Monoethanolamine (MEA), diglycolamine (DGA), diethanolamine (DEA), methyl diethanolamine (MDEA), triethanolamine (TEA), and blended aqueous solutions of these amines have been considered in our analyses. The required specification for the CO₂ capture process was 96 mole% CO₂ purity at the product for all simulations. The results are the optimum number of stages for the absorber and stripper columns, and the optimum absorbent concentration and operating conditions, i.e., the ones that give the minimum cost for CO₂ capture process. In this presentation, the comparison of the results obtained from both simulation-optimization techniques will be discussed. This comparison will provide the accuracy and the validity of the response surface technique results for the CO₂ capture process optimization. It should be noted that response surface methodology is simpler to develop and requires less expert knowledge compared to the ANN approach. Therefore, the response surface methodology can be used for CO₂ capture cost optimization if the results are closer to the global optimum obtained by the ANN approach.

Reference:

[1] Mofarahi, M., Khojasteh, Y., Khaledi, H., & Farahnak, A. (2008). Design of CO₂ absorption plant for recovery of CO₂ from flue gases of gas turbine. Energy, 33, 1311-1319.