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Selection of Controlled Variables for a Natural Gas to Liquids Process
Author(s) -
Mehdi Panahi,
Sigurd Skogestad
Publication year - 2012
Publication title -
industrial and engineering chemistry research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.878
H-Index - 221
eISSN - 1520-5045
pISSN - 0888-5885
DOI - 10.1021/ie202678h
Subject(s) - process (computing) , selection (genetic algorithm) , natural gas , process engineering , computer science , biochemical engineering , chemistry , machine learning , engineering , organic chemistry , operating system
The aim of this work is to select the best individual or combined controlled variables (CVs) for a natural gas to hydrocarbon liquids (GTL) process based on the idea of self-optimizing control. The objective function is to maximize the variable income of the plant, and two modes of operation are studied. In mode I, where the natural gas flow rate is given, there are three unconstrained degrees of freedom (DOFs) and the corresponding individual self-optimizing CVs are selected as (i) CO2 removal in fresh synthesis gas (syngas), (ii) CO mole fraction in fresh syngas, and (iii) CO mole fraction in recycle tail gas from the Fischer−Tropsch (FT) reactor. This set of CVs gives a worst-case loss of 1,393 USD/h. Adding one, two, and three measurements and controlling measurement combinations decrease the worst-case loss significantly, to 184, 161, and 53 USD/h, respectively. In mode II, the natural gas flow rate is a degree of freedom and it is optimal to increase it as much as possible to maximize profit. The variable income increases almost linearly until the oxygen flow rate becomes active. Practically, this is the maximum achievable income. Theoretically, it is possible to increase the natural gas flow rate to improve the objective function, but this results in large recycle flow rates to the FT reactor (similar to "snowballing") because its volume is the limitation.

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