Optimisation of K2CO3-based natural gas sweetening process: A hybrid Pareto and Fuzzy optimisation approach

Background: Natural gas is considered clean technology as compared to other fossil fuel resources. However, there is always a concern related to the carbon dioxide (CO2) removal via the gas sweetening unit. The current research focuses on enhancing the CO2 removal and reducing operating cost using a hybrid multi-objective optimisation technique, which incorporates (i) Pareto Front optimisation and (ii) Fuzzy optimisation. Method: Aspen Plus simulation is performed to simulate diethanolamine (DEA) promoted potassium carbonate (K2CO3)-based natural gas sweetening unit. A total of 1000 simulation samples are conducted to study the effect of solvent concentration, flowrate, and temperature on CO2 concentration in treated gas and operating cost. These solutions are fed into Pareto Front optimisation to determine sets of Pareto-optimal solutions. Thereafter, Fuzzy optimisation is performed to identify a single most optimal solution. Significant findings: The result showed that optimal solution with CO2 molar concentration in treated gas of 0.00006676 and operating cost of $19,495.08 h(-1) can be achieved at solvent concentration of 17.5 wt.%, flow-rate of 42,500 kmol h(-1), and temperature of 80 degrees C. The energy requirement per unit of CO2 removal for the final optimised solution was 19.31% less than that of the actual plant performance. (C) 2021 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.