Operation optimization of propane pre-cooled mixed refrigerant LNG Process: A novel integration of knowledge-based and constrained Bayesian optimization approaches

<p dir="ltr">Liquefied natural gas (LNG) technology, particularly the propane precooled mixed refrigerant (C3MR) process, has demonstrated efficiency and emerged as a distinctive dual-refrigerant technology widely used in LNG production. However, the liquefaction process is the highe...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي: Roba Shady (22048043) (author)
مؤلفون آخرون: Samer F. Ahmed (16931844) (author), Ahmad K. Sleiti (14778229) (author)
منشور في: 2024
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author Roba Shady (22048043)
author2 Samer F. Ahmed (16931844)
Ahmad K. Sleiti (14778229)
author2_role author
author
author_facet Roba Shady (22048043)
Samer F. Ahmed (16931844)
Ahmad K. Sleiti (14778229)
author_role author
dc.creator.none.fl_str_mv Roba Shady (22048043)
Samer F. Ahmed (16931844)
Ahmad K. Sleiti (14778229)
dc.date.none.fl_str_mv 2024-08-02T09:00:00Z
dc.identifier.none.fl_str_mv 10.1016/j.ces.2024.120560
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Operation_optimization_of_propane_pre-cooled_mixed_refrigerant_LNG_Process_A_novel_integration_of_knowledge-based_and_constrained_Bayesian_optimization_approaches/29900774
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Engineering
Chemical engineering
Propane pre-cooled mixed refrigerant
LNGMixed refrigerants
Knowledge-based Optimization
Constrained Bayesian optimization
Large-scale C3MR
dc.title.none.fl_str_mv Operation optimization of propane pre-cooled mixed refrigerant LNG Process: A novel integration of knowledge-based and constrained Bayesian optimization approaches
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">Liquefied natural gas (LNG) technology, particularly the propane precooled mixed refrigerant (C3MR) process, has demonstrated efficiency and emerged as a distinctive dual-refrigerant technology widely used in LNG production. However, the liquefaction process is the highest energy-intensive stage within its supply chain as it consumes about 8 % of the LNG energy content. Thus, for the first time, this study proposes systematic knowledge-based and constrained Bayesian optimization approaches to identify the optimal operation of the C3MR process. These approaches optimize both the operational parameters (pressures and flow rates) and the composition of the mixed refrigerant with practical equipment specifications and rigorous constraints. The results show that the specific energy consumption (SEC) is reduced to 0.264 kWh/kg<sub>LNG</sub>, which is 14.6 %, and 26 % lower than the basic C3MR process (unoptimized case) and typical industrial C3MR processes, respectively. In addition, the optimized SEC in this study is 14.5 % to 38.6 % lower than those reported in the literature. At large-scale LNG production (10,000 tons per day), the reduction in the SEC is translated into an 18 MW decrease in compression power, saving approximately 4.7 million $ per year for each C3MR train. Moreover, the coefficient of performance (COP) of the C3MR process was improved by about 15 %, and the CO<sub>2</sub> emissions were reduced by 17 % (7 tons per year) compared to the basic C3MR process, indicating potential advancements in large-scale LNG liquefaction processes.</p><h2>Other Information</h2><p dir="ltr">Published in: Chemical Engineering Science<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.ces.2024.120560" target="_blank">https://dx.doi.org/10.1016/j.ces.2024.120560</a></p>
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identifier_str_mv 10.1016/j.ces.2024.120560
network_acronym_str Manara2
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oai_identifier_str oai:figshare.com:article/29900774
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spelling Operation optimization of propane pre-cooled mixed refrigerant LNG Process: A novel integration of knowledge-based and constrained Bayesian optimization approachesRoba Shady (22048043)Samer F. Ahmed (16931844)Ahmad K. Sleiti (14778229)EngineeringChemical engineeringPropane pre-cooled mixed refrigerantLNGMixed refrigerantsKnowledge-based OptimizationConstrained Bayesian optimizationLarge-scale C3MR<p dir="ltr">Liquefied natural gas (LNG) technology, particularly the propane precooled mixed refrigerant (C3MR) process, has demonstrated efficiency and emerged as a distinctive dual-refrigerant technology widely used in LNG production. However, the liquefaction process is the highest energy-intensive stage within its supply chain as it consumes about 8 % of the LNG energy content. Thus, for the first time, this study proposes systematic knowledge-based and constrained Bayesian optimization approaches to identify the optimal operation of the C3MR process. These approaches optimize both the operational parameters (pressures and flow rates) and the composition of the mixed refrigerant with practical equipment specifications and rigorous constraints. The results show that the specific energy consumption (SEC) is reduced to 0.264 kWh/kg<sub>LNG</sub>, which is 14.6 %, and 26 % lower than the basic C3MR process (unoptimized case) and typical industrial C3MR processes, respectively. In addition, the optimized SEC in this study is 14.5 % to 38.6 % lower than those reported in the literature. At large-scale LNG production (10,000 tons per day), the reduction in the SEC is translated into an 18 MW decrease in compression power, saving approximately 4.7 million $ per year for each C3MR train. Moreover, the coefficient of performance (COP) of the C3MR process was improved by about 15 %, and the CO<sub>2</sub> emissions were reduced by 17 % (7 tons per year) compared to the basic C3MR process, indicating potential advancements in large-scale LNG liquefaction processes.</p><h2>Other Information</h2><p dir="ltr">Published in: Chemical Engineering Science<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.ces.2024.120560" target="_blank">https://dx.doi.org/10.1016/j.ces.2024.120560</a></p>2024-08-02T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.ces.2024.120560https://figshare.com/articles/journal_contribution/Operation_optimization_of_propane_pre-cooled_mixed_refrigerant_LNG_Process_A_novel_integration_of_knowledge-based_and_constrained_Bayesian_optimization_approaches/29900774CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/299007742024-08-02T09:00:00Z
spellingShingle Operation optimization of propane pre-cooled mixed refrigerant LNG Process: A novel integration of knowledge-based and constrained Bayesian optimization approaches
Roba Shady (22048043)
Engineering
Chemical engineering
Propane pre-cooled mixed refrigerant
LNGMixed refrigerants
Knowledge-based Optimization
Constrained Bayesian optimization
Large-scale C3MR
status_str publishedVersion
title Operation optimization of propane pre-cooled mixed refrigerant LNG Process: A novel integration of knowledge-based and constrained Bayesian optimization approaches
title_full Operation optimization of propane pre-cooled mixed refrigerant LNG Process: A novel integration of knowledge-based and constrained Bayesian optimization approaches
title_fullStr Operation optimization of propane pre-cooled mixed refrigerant LNG Process: A novel integration of knowledge-based and constrained Bayesian optimization approaches
title_full_unstemmed Operation optimization of propane pre-cooled mixed refrigerant LNG Process: A novel integration of knowledge-based and constrained Bayesian optimization approaches
title_short Operation optimization of propane pre-cooled mixed refrigerant LNG Process: A novel integration of knowledge-based and constrained Bayesian optimization approaches
title_sort Operation optimization of propane pre-cooled mixed refrigerant LNG Process: A novel integration of knowledge-based and constrained Bayesian optimization approaches
topic Engineering
Chemical engineering
Propane pre-cooled mixed refrigerant
LNGMixed refrigerants
Knowledge-based Optimization
Constrained Bayesian optimization
Large-scale C3MR