Modeling and Optimization of Natural Gas (NG) Liquefaction Process Using Surrogate Modeling Approach

Given the importance of liquefaction processes in the liquid natural gas (LNG) value chain, it is necessary to model the complexity of such process. A key stage in this system is the mixed refrigerant (MR) cycle that is used to liquify the natural gas in the liquefaction process. MR refrigeration cycle consists of compressors and heat exchangers in different compression stages that modify the properties of the MR by reducing its temperature and increasing its pressure. This super-cooled and super-pressurized stream when passing in countercurrent in heat exchanging stage in the liquefaction section transform the natural gas stream into its liquid state LNG. In this work, the use of surrogate models is addressed for the compressor’s power consumption and efficiency formulations along with the heat exchanger’s performance in terms of heat duty after each compression stage. The surrogates built herein are shown to be sufficiently accurate to employed in decision-making environments such as simulation, optimization, and control. The industrial modeling and programming language (IMPL) is used to build the optimization models for the surrogate and rigorous models, which showed small error percentages for the optimal values of both models. The optimization model objective is to get optimal operability values for the compressors power consumption and efficiency as well as the heat exchangers heat duty performance by providing the proper operating values. The aim of this thesis is to model and optimize the MR cycle for the manufacturing of the liquified natural gas including the compressors and heat exchangers at the MR cycle using a simpler approach than the complex approaches that aids the critical decision-making process in a timely manner.