Waste heat harness in a thermal energy system using TEGs, and SCO2 brayton cycle driven by renewable sources for electricity and liquid hydrogen Production: Thermo-Economic optimization using ANNs
This research introduces an innovative thermal energy system that combines solar and wind energy to produce electricity, generate hydrogen, and facilitate liquefaction. This system includes a parabolic trough solar collector (PTSC) that heats nitrate salts, transferring the thermal energy to a super...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-08-01
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| Series: | Case Studies in Thermal Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X2500629X |
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| author | Amr S. Abouzied Sarminah Samad Pradeep Kumar Singh Ahmed H. Janabi Mohamed Shaban Asma Ahmed A. Mohammed Shoira Formanova H. Elhosiny Ali Samah G. Babiker Abdulrahman M. Alansari |
| author_facet | Amr S. Abouzied Sarminah Samad Pradeep Kumar Singh Ahmed H. Janabi Mohamed Shaban Asma Ahmed A. Mohammed Shoira Formanova H. Elhosiny Ali Samah G. Babiker Abdulrahman M. Alansari |
| author_sort | Amr S. Abouzied |
| collection | DOAJ |
| description | This research introduces an innovative thermal energy system that combines solar and wind energy to produce electricity, generate hydrogen, and facilitate liquefaction. This system includes a parabolic trough solar collector (PTSC) that heats nitrate salts, transferring the thermal energy to a supercritical carbon dioxide Brayton cycle (SCO2-BC). Furthermore, thermoelectric generators (TEG) are integrated to capture energy from waste heat sources. Additionally, this study breaks new ground by incorporating solar and wind power with a supercritical CO2 cycle alongside hydrogen liquefaction, a field that is still relatively uncharted. A detailed techno-economic and environmental model is utilized to assess the system's performance, concentrating on critical indicators such as second law efficiency, total cost rate, hydrogen production rate, net power output, levelized costs, and the rate of CO2 emission reduction. Following this, an optimization process is carried out using a genetic algorithm to investigate two different scenarios. Finally, the LINMAP method is applied to identify optimal solutions for each scenario. The study reveals that the system generated a grid power output of 461.2 kW and produced 8.3 kg of liquid hydrogen per hour. The overall cost of operation was established at 103.8 $/h with an exergy efficiency of 16.2 %. Further refinements resulted in values of 19.33 % for second-law efficiency, 124.80 $/h for cost rate, and 1021.64 kW for grid power. |
| format | Article |
| id | doaj-art-9a1bb2f63fed48f081db12e862dd9ee8 |
| institution | DOAJ |
| issn | 2214-157X |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Case Studies in Thermal Engineering |
| spelling | doaj-art-9a1bb2f63fed48f081db12e862dd9ee82025-08-20T03:08:59ZengElsevierCase Studies in Thermal Engineering2214-157X2025-08-017210636910.1016/j.csite.2025.106369Waste heat harness in a thermal energy system using TEGs, and SCO2 brayton cycle driven by renewable sources for electricity and liquid hydrogen Production: Thermo-Economic optimization using ANNsAmr S. Abouzied0Sarminah Samad1Pradeep Kumar Singh2Ahmed H. Janabi3Mohamed Shaban4Asma Ahmed A. Mohammed5Shoira Formanova6H. Elhosiny Ali7Samah G. Babiker8Abdulrahman M. Alansari9Department of Pharmaceutical Chemistry, College of Pharmacy, University of Hail, Hail, 81442, Saudi ArabiaDepartment of Management, College of Business Administration, Princess Nourah Bint Abdulrahman University, Riyadh, 11671, Saudi Arabia; Corresponding author.Department of Mechanical Engineering, Institute of Engineering & Technology, GLA University, Mathura, U.P., 281406, IndiaComputer Techniques Engineering Department, College of Engineering & Technology, Al-Mustaqbal University, Babylon, IraqDepartment of Physics, Faculty of Science, Islamic University of Madinah, Madinah, 42351, Saudi Arabia; Corresponding author.Department of Computer Science, University of Tabuk, Saudi ArabiaDepartment of Chemistry and Its Teaching Methods, Tashkent State Pedagogical University, Tashkent, UzbekistanPhysics Department, Faculty of Science, King Khalid University, P.O. Box 9004, Abha, Saudi ArabiaDepartment of Electronic Physics, Faculty of Applied Science, Red Sea University, Port Sudan, Sudan; Corresponding author.Department of Mechanical Engineering, College of Engineering, University of Business and Technology, Jeddah, 21361, Saudi ArabiaThis research introduces an innovative thermal energy system that combines solar and wind energy to produce electricity, generate hydrogen, and facilitate liquefaction. This system includes a parabolic trough solar collector (PTSC) that heats nitrate salts, transferring the thermal energy to a supercritical carbon dioxide Brayton cycle (SCO2-BC). Furthermore, thermoelectric generators (TEG) are integrated to capture energy from waste heat sources. Additionally, this study breaks new ground by incorporating solar and wind power with a supercritical CO2 cycle alongside hydrogen liquefaction, a field that is still relatively uncharted. A detailed techno-economic and environmental model is utilized to assess the system's performance, concentrating on critical indicators such as second law efficiency, total cost rate, hydrogen production rate, net power output, levelized costs, and the rate of CO2 emission reduction. Following this, an optimization process is carried out using a genetic algorithm to investigate two different scenarios. Finally, the LINMAP method is applied to identify optimal solutions for each scenario. The study reveals that the system generated a grid power output of 461.2 kW and produced 8.3 kg of liquid hydrogen per hour. The overall cost of operation was established at 103.8 $/h with an exergy efficiency of 16.2 %. Further refinements resulted in values of 19.33 % for second-law efficiency, 124.80 $/h for cost rate, and 1021.64 kW for grid power.http://www.sciencedirect.com/science/article/pii/S2214157X2500629XWaste heat recoveryThermal energy utilizationParabolic trough solar collectorsThermoelectric generatorsClaude liquid hydrogen productionArtificial neural networks and genetic algorithm |
| spellingShingle | Amr S. Abouzied Sarminah Samad Pradeep Kumar Singh Ahmed H. Janabi Mohamed Shaban Asma Ahmed A. Mohammed Shoira Formanova H. Elhosiny Ali Samah G. Babiker Abdulrahman M. Alansari Waste heat harness in a thermal energy system using TEGs, and SCO2 brayton cycle driven by renewable sources for electricity and liquid hydrogen Production: Thermo-Economic optimization using ANNs Case Studies in Thermal Engineering Waste heat recovery Thermal energy utilization Parabolic trough solar collectors Thermoelectric generators Claude liquid hydrogen production Artificial neural networks and genetic algorithm |
| title | Waste heat harness in a thermal energy system using TEGs, and SCO2 brayton cycle driven by renewable sources for electricity and liquid hydrogen Production: Thermo-Economic optimization using ANNs |
| title_full | Waste heat harness in a thermal energy system using TEGs, and SCO2 brayton cycle driven by renewable sources for electricity and liquid hydrogen Production: Thermo-Economic optimization using ANNs |
| title_fullStr | Waste heat harness in a thermal energy system using TEGs, and SCO2 brayton cycle driven by renewable sources for electricity and liquid hydrogen Production: Thermo-Economic optimization using ANNs |
| title_full_unstemmed | Waste heat harness in a thermal energy system using TEGs, and SCO2 brayton cycle driven by renewable sources for electricity and liquid hydrogen Production: Thermo-Economic optimization using ANNs |
| title_short | Waste heat harness in a thermal energy system using TEGs, and SCO2 brayton cycle driven by renewable sources for electricity and liquid hydrogen Production: Thermo-Economic optimization using ANNs |
| title_sort | waste heat harness in a thermal energy system using tegs and sco2 brayton cycle driven by renewable sources for electricity and liquid hydrogen production thermo economic optimization using anns |
| topic | Waste heat recovery Thermal energy utilization Parabolic trough solar collectors Thermoelectric generators Claude liquid hydrogen production Artificial neural networks and genetic algorithm |
| url | http://www.sciencedirect.com/science/article/pii/S2214157X2500629X |
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