4.6 Article

Design and optimization of distillation column sequencing for the GTL process

期刊

CHEMICAL ENGINEERING RESEARCH & DESIGN
卷 173, 期 -, 页码 119-128

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ELSEVIER
DOI: 10.1016/j.cherd.2021.06.020

关键词

GTL distillation unit; Process design automation; Separation matrix; Inside-out algorithm; Fuel production

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The study aimed to optimize the distillation column configuration for GTL distillation unit and developed distillation simulation code based on inside-out algorithm and rigorous method. Genetic algorithm was used to minimize the hybrid TAC function. Results showed that direct configuration performed the best overall evaluation and reduced operating costs by 26%.
Gas to liquid (GTL) is one of the main processes that liquefied natural gas through chemical conversion into synthetic crude that can be upgraded and separated into different useful hydrocarbons. The present study has been carried out to optimize the distillation column configuration and applied it to the GTL distillation unit. The distillation simulation code has been developed in two main parts, shortcut and rigorous based on inside-out algo-rithm. A modular design approach is presented in which the code is developed in only one computational environment. Compared to the existing methods, the uniform code avoids time-wasting data transmission between different commercial software. Therefore, the developed code includes all three main steps, generation, simulation and optimization, which are interconnected to achieve the best sequence according to the objective function. The genetic algorithm is utilized to minimize the hybrid TAC function that checks products specifications simultaneously. The results demonstrate the capacity of direct configuration that performances the best overall evaluation parts of TAC, operating costs, capital costs, and exergy losses, therefore it reduces up to 26% in operating cost compared with indirect configuration which is the most commonly used sequence in GTL plant. (c) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

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