Multi-objective optimization of FCC separation system based on NSGA-II

Based on the industrial production data, the simulation of the separation process of a 2 million tons/year FCC unit including the fractionation and the absorption-stabilization systems were conducted on Aspen Plus software. To optimize the operation process, multi-objective optimization was performed integrating the Aspen Plus platform and MATLAB environment utilizing the improved non-dominated sorting genetic algorithm (NSGA-II). The established multi-objective optimization model was used for the operating variable screening, the genetic algebra selection and the optimal solution determination. During the optimization, the total yield of LPG and stable gasoline was aimed as the first optimization objective while the energy consumption of the whole system as the second objective. Five expressions were applied as the constraint functions and nine operating variables were conducted as the decision variables. The results showed that the performances of FCC separation system have been greatly improved after optimization. Some optimization strategies are advised for the whole system. The total yield of LPG and stabilized gasoline increases by 2. 44 %, and the energy consumption of the separation system decreases by 41. 79 %. In addition, the CO2 emission is reduced by 23.59 t/h and the total annual cost (TAC) is reduced by $0.89 million/year. It has been revealed that the multi-objective optimization method based on NSGA-II algorithm is useful for the guidance of the optimization of industrial petrochemical process.