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Among all large-scale natural gas (NG) liquefaction processes, the mixed fluid cascade (MFC) process is recognized as a best-alternative option for the LNG production, mainly due its competitive performance. However, from a thermodynamic point of view, the MFC process is still far from its potential maximum energy efficiency due to non-optimal execution of design variables. Therefore, the energy efficiency enhancement of the MFC process remains an ongoing issue. The design optimization after fixing the main configuration of the process is one of the most economic, but challenging exercises during the design stages. In this study, shuffled complex evolution (SCE) is studied to find the optimal design of the MFC process corresponding to minimal energy consumption in refrigeration cycles. The MFC process is simulated using Aspen Hysys® v10 and then coupled with the SCE approach, which is coded in MATLAB® 2019a. The refrigerant composition and operating pressures for each cycle of the MFC process were optimized considering the approach temperature inside the LNG heat exchanger as a constraint. The resulting optimal MFC process saved 19.76% overall compression power and reduced the exergy destruction up to 28.76%. The thermodynamic efficiency (figure of merit) of the SCE-optimized process was 25% higher than that of the published base case. Furthermore, the optimization results also imply that there is a trade-off between the thermodynamic performance improvement and the computational cost (no. of iterations). In conclusion, SCE exhibited potential to improve the performance of highly nonlinear and complex processes such as LNG processes.

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Propane-Precooled Mixed Refrigerant (C3MR) and Single Mixed Refrigerant (SMR) processes are considered as optimal choices for onshore and offshore natural gas liquefaction, respectively. However, from thermodynamics point of view, these processes are still far away from their maximum achievable energy efficiency due to nonoptimal execution of the design variables. Therefore, Liquefied Natural Gas (LNG) production is considered as one of the energy-intensive cryogenic industries. In this context, this study examines a single-solution-based Vortex Search (VS) approach to find the optimal design variables corresponding to minimal energy consumption for LNG processes, i.e., C3MR and SMR. The LNG processes are simulated using Aspen Hysys and then linked with VS algorithm, which is coded in MATLAB. The results indicated that the SMR process is a potential process for offshore sites that can liquefy natural gas with 16.1% less energy consumption compared with the published base case. Whereas, for onshore LNG production, the energy consumption for the C3MR process is reduced up to 27.8% when compared with the previously published base case. The optimal designs of the SMR and C3MR processes are also found via distinctive well-established optimization approaches (i.e., genetic algorithm and particle swarm optimization) and their performance is compared with that of the VS methodology. The authors believe this work will greatly help the process engineers overcome the challenges relating to the energy efficiency of LNG industry, as well as other mixed refrigerant-based cryogenic processes.