Gas Processing, Volume (9), No (1), Year (2021-6) , Pages (157-172)

Title : ( Modeling and Optimization of Different Acid Gas Enrichment Structures via Coupling of Response Surface Method with Genetic Algorithm )

Authors: maryam pahlavan , Akbar Shahsavand , Mehdi Panahi ,

Citation: BibTeX | EndNote

Abstract

: Lean acid gases entering any sulfur recovery unit (SRU) can strongly damage the corresponding overall sulfur efficiency. The use of the acid gas enrichment (AGE) process is essential to increase recovery efficiency. Two novel scenarios are studied in the present work. The first low-pressure structure uses an enrichment tower with operating pressure above the atmosphere and lower than the regenerator pressure, while, the second high-pressure scenario limits the enrichment tower pressure between the amine flash drum and corresponding regenerator pressures. The combination of the Aspen-HYSYS process simulator and response surface method is successfully employed to generate training data and create reliable hypersurfaces for mimicking the acid gas enrichment rate versus various operating parameters. An initial sensitivity analysis is recruited to pinpoint the most dominant input parameters. The optimization of fitted merit functions was carried out using our in-house genetic algorithm code. The corresponding enrichments for high and low-pressure scenarios were 83.63 and 70.53% respectively. These are more than 140% and 105% increases in H2S concentrations in comparison to the conventional design of the existing SRUs, which is based on around 34% H2S content in the acid gas feed. Economic and environmental evaluations of both scenarios revealed that the optimal low-pressure structure is much more favorable from the economic point of view, while the high-pressure design performs more environmentally friendly by reducing the SO2 emissions by at least 21.4%. To the best of our knowledge, the above complex and detailed study have never been performed previously for any AGE process.

Keywords

Acid Gas Enrichment; SO2 emissions; Genetic Algorithm; Response Surface Method; Neural Network
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@article{paperid:1092652,
author = {Pahlavan, Maryam and Akbar Shahsavand, and Panahi, Mehdi},
title = {Modeling and Optimization of Different Acid Gas Enrichment Structures via Coupling of Response Surface Method with Genetic Algorithm},
journal = {Gas Processing},
year = {2021},
volume = {9},
number = {1},
month = {June},
issn = {2322-3251},
pages = {157--172},
numpages = {15},
keywords = {Acid Gas Enrichment; SO2 emissions; Genetic Algorithm; Response Surface Method; Neural Network},
}

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%0 Journal Article
%T Modeling and Optimization of Different Acid Gas Enrichment Structures via Coupling of Response Surface Method with Genetic Algorithm
%A Pahlavan, Maryam
%A Akbar Shahsavand,
%A Panahi, Mehdi
%J Gas Processing
%@ 2322-3251
%D 2021

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