Energy optimization for single mixed refrigerant natural gas liquefaction process using the metaheuristic vortex search algorithm

Abstract

A metaheuristic vortex search algorithm was investigated for the optimization of a single mixed refrigerant (SMR) natural gas liquefaction process. The optimal design of a natural gas liquefaction processes involves multivariable non-linear thermodynamic interactions, which lead to exergy destruction and contribute to process irreversibility. As key decision variables, the optimal values of mixed refrigerant flow rates and process operating pressures were determined in the vortex pattern corresponding to the minimum required energy. In addition, the rigorous SMR process was simulated using Aspen Hysys® software and the resulting model was connected with the vortex search optimization algorithm coded in MATLAB. The optimal operating conditions found by the vortex search algorithm significantly reduced the required energy of the single mixed refrigerant process by ≤41.5% and improved the coefficient of performance by ≤32.8% in comparison with the base case. The vortex search algorithm was also compared with other well-proven optimization algorithms, such as genetic and particle swarm optimization algorithms, and was found to exhibit a superior performance over these existing approaches.