Abstract

This chapter provides a brief review of the developments in the optimization of Natural gas (NG) liquefaction techniques since 2001. NG liquefaction is energy intensive and small improvements in liquefaction efficiency brings huge cost benefits thus optimization is needed. To tackle the NG liquefaction optimization problem, two different optimization philosophies, i) deterministic and ii) stochastic, have been adopted. The limitations of the deterministic approach have paved the way for derivative-free stochastic approaches. Although both techniques work well for the reported problem, their application is limited to the specific problems and generalization is quite difficult. Therefore to overcome this problem, a third of the so called knowledge-inspired class have been evolved for NG liquefaction optimization. Thus, this chapter covers the major development that took place in NG liquefaction area and after reviewing the trends future research directions are given.

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