천연가스 액화공정의 최적화와 분석

Natural gas liquefaction is one of highly energy-intensive processes throughout the overall natural gas supply chain. The optimization of the liquefaction processes offers a lot of opportunities to reduce the operational and capital costs. Thus, many previous studies have tackled this kind of problems of optimizing natural gas liquefaction process conditions and have also suggested new liquefaction processes. In this study a single mixed refrigerant (SMR) process on the LNG FPSO is optimized using genetic algorithm. The objective function value (OFV) of the problem is the total energy consumption, and the variables including operational conditions (pressures, temperatures and flowrates) and the composition values of the mixed refrigerant used in this process are considered to solve this optimization problem. In addition, an analysis procedure fully using the merits of genetic algorithm is suggested to evaluate the optimization results.