Computer-based optimization of acid gas removal unit using modified CO₂ absorption kinetic models

Parameter estimation in models plays an important role in the development of mathematical models capable of accurate simulation and genuine optimization of real-world processes. This paper presents the results of a computer based optimization of the operation of a commercial acid gas removal unit that uses amine as solvent. The kinetics of CO₂ absorption using Methyldiethanolamine (MDEA) populating an existing model is revisited based on real-data-driven parameters re-estimation. The latter is achieved via an evolutionary technique that uses Particle Swarm Optimization (PSO) algorithm. The new CO₂ kinetic model is then embedded in a first-principle process simulation model and used to quantify and analyze the effects of certain process parameters such as amine circulation rate, amine concentration, lean amine temperature and rich amine temperature on the unit performance and efficiency. Also, patterns of various plant performance indicators such as sweet gas composition profile, reboiler steam rate, pumping and cooling requirements are plotted against the abovementioned parameters and respective optimum conditions are proposed, based on the computer simulation results. Further comprehensive analysis is performed to assess the net monetary benefit of implementing these proposed changes for the studied chemical process.