Enhanced hydrogen generation in a combined hybrid cycle using aluminum and cooper oxide nanomaterial based on biomass and vanadium chloride cycle: Optimization based on deep learning techniques and Environmental appraisal
The usage of Nanofluid to enhance heat transfer has been investigated by many re-searchers in small-scale heat transfers; however, in large-scale power plants, it has not been taken care of. In this research paper, a newly proposed energy system for hydrogen generation based on renewable sources is...
Published in: | INTERNATIONAL JOURNAL OF HYDROGEN ENERGY |
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Main Authors: | , , , , , , , , , , |
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Language: | English |
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PERGAMON-ELSEVIER SCIENCE LTD
2024
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Online Access: | https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001139535000001 |
author |
Zhou Jincheng; Ali Masood Ashraf; Hai Tao; Sharma Kamal; Aziz Kosar Hama; Alyousuf Farah Qasim Ahmed; Almoalimi Khaled Twfiq; Almojil Sattam Fahad; Almohana Abdulaziz Ibrahim; Alali Abdulrhman Fahmi |
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spellingShingle |
Zhou Jincheng; Ali Masood Ashraf; Hai Tao; Sharma Kamal; Aziz Kosar Hama; Alyousuf Farah Qasim Ahmed; Almoalimi Khaled Twfiq; Almojil Sattam Fahad; Almohana Abdulaziz Ibrahim; Alali Abdulrhman Fahmi Enhanced hydrogen generation in a combined hybrid cycle using aluminum and cooper oxide nanomaterial based on biomass and vanadium chloride cycle: Optimization based on deep learning techniques and Environmental appraisal Chemistry; Electrochemistry; Energy & Fuels |
author_facet |
Zhou Jincheng; Ali Masood Ashraf; Hai Tao; Sharma Kamal; Aziz Kosar Hama; Alyousuf Farah Qasim Ahmed; Almoalimi Khaled Twfiq; Almojil Sattam Fahad; Almohana Abdulaziz Ibrahim; Alali Abdulrhman Fahmi |
author_sort |
Zhou |
spelling |
Zhou, Jincheng; Ali, Masood Ashraf; Hai, Tao; Sharma, Kamal; Aziz, Kosar Hama; Alyousuf, Farah Qasim Ahmed; Almoalimi, Khaled Twfiq; Almojil, Sattam Fahad; Almohana, Abdulaziz Ibrahim; Alali, Abdulrhman Fahmi Enhanced hydrogen generation in a combined hybrid cycle using aluminum and cooper oxide nanomaterial based on biomass and vanadium chloride cycle: Optimization based on deep learning techniques and Environmental appraisal INTERNATIONAL JOURNAL OF HYDROGEN ENERGY English Article The usage of Nanofluid to enhance heat transfer has been investigated by many re-searchers in small-scale heat transfers; however, in large-scale power plants, it has not been taken care of. In this research paper, a newly proposed energy system for hydrogen generation based on renewable sources is proposed and analyzed in detail. Unlike other power input systems, the vanadium chloride system generates hydrogen because it uses waste heat. In this regard, the nanoparticles of Al2O3 and CuO are utilized in the main heat exchanger to enhance the heat transfer to the reactor of VCLC to generate more hydrogen. Also, the compound system has the gasifier-based internally fired gas turbine as the main system and can generate hydrogen in a more green way. The optimization based on deep learning methods is applied to seek the highest point of operation by the system. The results exhibit that Al2O3 causes more heat transfer and efficiency enhancement, thus in hydrogen production, causing an increase of 18.5% compared to base fluid and 8.3% compared to CuO in H2 Generation In circumstances when it is optimal, the values for exergetic efficiency and total hydrogen production are 64.5% and 4.5 kg/s respectively. In addition, using a nanofluid heat exchanger and biomass energy reduces CO2 emissions to 0.91 kg/kWh. (c) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved. PERGAMON-ELSEVIER SCIENCE LTD 0360-3199 1879-3487 2024 52 10.1016/j.ijhydene.2022.10.181 Chemistry; Electrochemistry; Energy & Fuels WOS:001139535000001 https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001139535000001 |
title |
Enhanced hydrogen generation in a combined hybrid cycle using aluminum and cooper oxide nanomaterial based on biomass and vanadium chloride cycle: Optimization based on deep learning techniques and Environmental appraisal |
title_short |
Enhanced hydrogen generation in a combined hybrid cycle using aluminum and cooper oxide nanomaterial based on biomass and vanadium chloride cycle: Optimization based on deep learning techniques and Environmental appraisal |
title_full |
Enhanced hydrogen generation in a combined hybrid cycle using aluminum and cooper oxide nanomaterial based on biomass and vanadium chloride cycle: Optimization based on deep learning techniques and Environmental appraisal |
title_fullStr |
Enhanced hydrogen generation in a combined hybrid cycle using aluminum and cooper oxide nanomaterial based on biomass and vanadium chloride cycle: Optimization based on deep learning techniques and Environmental appraisal |
title_full_unstemmed |
Enhanced hydrogen generation in a combined hybrid cycle using aluminum and cooper oxide nanomaterial based on biomass and vanadium chloride cycle: Optimization based on deep learning techniques and Environmental appraisal |
title_sort |
Enhanced hydrogen generation in a combined hybrid cycle using aluminum and cooper oxide nanomaterial based on biomass and vanadium chloride cycle: Optimization based on deep learning techniques and Environmental appraisal |
container_title |
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY |
language |
English |
format |
Article |
description |
The usage of Nanofluid to enhance heat transfer has been investigated by many re-searchers in small-scale heat transfers; however, in large-scale power plants, it has not been taken care of. In this research paper, a newly proposed energy system for hydrogen generation based on renewable sources is proposed and analyzed in detail. Unlike other power input systems, the vanadium chloride system generates hydrogen because it uses waste heat. In this regard, the nanoparticles of Al2O3 and CuO are utilized in the main heat exchanger to enhance the heat transfer to the reactor of VCLC to generate more hydrogen. Also, the compound system has the gasifier-based internally fired gas turbine as the main system and can generate hydrogen in a more green way. The optimization based on deep learning methods is applied to seek the highest point of operation by the system. The results exhibit that Al2O3 causes more heat transfer and efficiency enhancement, thus in hydrogen production, causing an increase of 18.5% compared to base fluid and 8.3% compared to CuO in H2 Generation In circumstances when it is optimal, the values for exergetic efficiency and total hydrogen production are 64.5% and 4.5 kg/s respectively. In addition, using a nanofluid heat exchanger and biomass energy reduces CO2 emissions to 0.91 kg/kWh. (c) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved. |
publisher |
PERGAMON-ELSEVIER SCIENCE LTD |
issn |
0360-3199 1879-3487 |
publishDate |
2024 |
container_volume |
52 |
container_issue |
|
doi_str_mv |
10.1016/j.ijhydene.2022.10.181 |
topic |
Chemistry; Electrochemistry; Energy & Fuels |
topic_facet |
Chemistry; Electrochemistry; Energy & Fuels |
accesstype |
|
id |
WOS:001139535000001 |
url |
https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001139535000001 |
record_format |
wos |
collection |
Web of Science (WoS) |
_version_ |
1809678579248660480 |