The structure of the thesis is outlined in the following. Chapter 2 deals with the modeling of LNG plants. The most importance lies on the model of the spi-ral wound heat exchangers as they are the major equipment of most baseload LNG plants. In Chapter 3, the concept of self-optimizing control is introduced and the problem of nding best controlled variable sets is discussed. Publicly available solution methods are reviewed and new advanced methods are pro-posed. In order to illustrate the advantage of the latter, they are compared with the former by repeated random tests. Their application to a academic process example and three LNG liquefaction processes takes place in Chapter 4. The results are new sets of controlled variables which provide almost op-timal operation of the considered processes when a constant setpoint policy is applied. For the most promising controlled variable sets of the LIMUM® cycle and the MFC® processes, the best pairings with the manipulated vari-ables are gured out in Chapter 5 by means of dynamical measures of the linearized dynamic model equations. The dynamical performance of these new control strategies is compared with conventional ones. Concluding remarks and outlook for future work are given chapter-specic in Sections 2.4.8, 3.6, 4.8, 5.6.
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Modeling
The investigation of the operation of LNG liquefaction processes is based on dynamical simulation models of these processes. The models used throughout this thesis are built in the Linde in-house simulator OPTISIM®. This Chapter gives an overview on property calculation for mixtures of hydrocarbons and governing equations for standard unit operations present in LNG liquefaction processes. Section 2.1 refers to prior work in the eld of modeling of LNG liquefaction processes. Section 2.2 deals with the calculation of properties of natural gas and mixed refrigerants. In Section 2.3, a survey of modeling of unit operations present in LNG liquefaction processes is given. The further development of a spiral wound heat exchanger model is presented in Section 2.4. Some issues concerning the modeling of cycle processes are discussed in Section 2.5.