APCI- LNG single mixed refrigerant process for natural gas liquefaction cycle: Analysis and optimization

• Genetic algorithm was applied to minimize energy consumption of an APCI process.
• A linear relationship between MR composition and total required work was obtained.
• Change in ambient temperature and feed pressure affects the MR composition.
• Total work is correlated with ambient temperature via a second order polynomial.

In this paper, a typical single mixed refrigerant (SMR) with low energy consumption is analyzed to determine the optimum operating conditions. Genetic Algorithm (GA) tool is used to minimize the total required work by optimizing eleven variables including the outlet pressures of all compressors and throttling valves and the molar flow rate of the MR components. The results of the process simulation show that the total work is varied linearly by the compositions. It is observed that to have a minimum work, when the ambient temperature increases, the compositions of both methane and ethane should be decreased, while those of nitrogen, propane and n-butane should be increased. Moreover, optimized values of the total required work at different ambient temperatures were correlated with a second order polynomial. Increasing feed pressure has small effect on the MR compositions, but significant effect on the total work.