Waste heat recovery cycles integration into a net-Zero emission solar-thermal multi-generation system; Techno-economic analysis and ANN-MOPSO optimization
This paper presents a novel solar-powered multi-generation system (MGS) integrated with a fuel cell, designed to enhance both sustainability and operational reliability. A significant limitation of solar energy is its intermittency, as sunlight is only available during specific hours of the day. To...
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Elsevier
2025-02-01
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| Series: | Case Studies in Thermal Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X24017210 |
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| author | Pradeep Kumar Singh Ali Basem Rebwar Nasir Dara Mohamed Shaban Sarminah Samad Raymond Ghandour Ahmad Almadhor Samah G. Babiker Iskandar Shernazarov Ibrahim A. Alsayer |
| author_facet | Pradeep Kumar Singh Ali Basem Rebwar Nasir Dara Mohamed Shaban Sarminah Samad Raymond Ghandour Ahmad Almadhor Samah G. Babiker Iskandar Shernazarov Ibrahim A. Alsayer |
| author_sort | Pradeep Kumar Singh |
| collection | DOAJ |
| description | This paper presents a novel solar-powered multi-generation system (MGS) integrated with a fuel cell, designed to enhance both sustainability and operational reliability. A significant limitation of solar energy is its intermittency, as sunlight is only available during specific hours of the day. To address this constraint, hydrogen energy is incorporated into the system to facilitate continuous operation through the fuel cell. The proposed MGS efficiently utilizes waste heat recovery cycles to simultaneously produce electricity, fresh water, cooling, and heating. The system consists of parabolic trough solar collectors, a steam Rankine cycle, an organic Rankine cycle, an absorption chiller, a reverse osmosis desalination unit, and a fuel cell coupled with an organic Rankine cycle-thermoelectric generator. Upon validating the primary components, the system is thoroughly evaluated in terms of energy, exergy, and economic performance, and a parametric study is conducted to assess the influence of key operational parameters. The analysis identifies the solar cycle as having the highest irreversibility, accounting for 55.2 %, and the highest cost rate, contributing 44.1 % among the subsystems. To optimize the system's performance, an artificial neural network is integrated with a multi-objective particle swarm optimization algorithm to reduce computational time from approximately 16 h to 4 min. Finally, under optimal conditions, the system achieves an exergy efficiency of 31.69 %, freshwater production of 19.53 kg/s, cooling production of 441.6 kW, and a total cost rate of $87.2/h. |
| format | Article |
| id | doaj-art-21641bdd2ca047fe8da46f057107be78 |
| institution | Kabale University |
| issn | 2214-157X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Case Studies in Thermal Engineering |
| spelling | doaj-art-21641bdd2ca047fe8da46f057107be782025-02-02T05:27:11ZengElsevierCase Studies in Thermal Engineering2214-157X2025-02-0166105690Waste heat recovery cycles integration into a net-Zero emission solar-thermal multi-generation system; Techno-economic analysis and ANN-MOPSO optimizationPradeep Kumar Singh0Ali Basem1Rebwar Nasir Dara2Mohamed Shaban3Sarminah Samad4Raymond Ghandour5Ahmad Almadhor6Samah G. Babiker7Iskandar Shernazarov8Ibrahim A. Alsayer9Department of Mechanical Engineering, Institute of Engineering & Technology, GLA University, Mathura, U.P., 281406, India; Corresponding author.Faculty of Engineering, Warith Al-Anbiyaa University, Karbala, 56001, IraqDepartment of Earth sciences and petroleum, College of Science, Salahaddin University-Erbil, Erbil, 44002, Iraq; Department of Petroleum Engineering, College of Engineering, Knowledge University, Erbil, IraqDepartment of Physics, Faculty of Science, Islamic University of Madinah, Madinah, 42351, Saudi Arabia; Corresponding author. Department of Physics, Faculty of Science, Islamic University of Madinah, Madinah 42351, Saudi Arabia.Department of Management, College of Business Administration, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia; Corresponding author. Department of Management, College of Business Administration, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia.College of Engineering and Technology, American University of the Middle East, 54200, Egaila, KuwaitDepartment of Computer Engineering and Networks, College of Computer and Information Sciences, Jouf University, Saudi ArabiaDepartment of Electronic Physics, Faculty of Applied Science, Red Sea University, Port Sudan, Sudan; Corresponding author.Department of Chemistry and Its Teaching Methods, Tashkent State Pedagogical University, Tashkent, UzbekistanDepartment of Chemical and Materials Engineering, Engineering College, Northern Border University, Arar, 91431, Saudi ArabiaThis paper presents a novel solar-powered multi-generation system (MGS) integrated with a fuel cell, designed to enhance both sustainability and operational reliability. A significant limitation of solar energy is its intermittency, as sunlight is only available during specific hours of the day. To address this constraint, hydrogen energy is incorporated into the system to facilitate continuous operation through the fuel cell. The proposed MGS efficiently utilizes waste heat recovery cycles to simultaneously produce electricity, fresh water, cooling, and heating. The system consists of parabolic trough solar collectors, a steam Rankine cycle, an organic Rankine cycle, an absorption chiller, a reverse osmosis desalination unit, and a fuel cell coupled with an organic Rankine cycle-thermoelectric generator. Upon validating the primary components, the system is thoroughly evaluated in terms of energy, exergy, and economic performance, and a parametric study is conducted to assess the influence of key operational parameters. The analysis identifies the solar cycle as having the highest irreversibility, accounting for 55.2 %, and the highest cost rate, contributing 44.1 % among the subsystems. To optimize the system's performance, an artificial neural network is integrated with a multi-objective particle swarm optimization algorithm to reduce computational time from approximately 16 h to 4 min. Finally, under optimal conditions, the system achieves an exergy efficiency of 31.69 %, freshwater production of 19.53 kg/s, cooling production of 441.6 kW, and a total cost rate of $87.2/h.http://www.sciencedirect.com/science/article/pii/S2214157X24017210Waste heat recoveryHeat energySolar-based systemFuel cellMulti-generation systemMulti-objective optimization |
| spellingShingle | Pradeep Kumar Singh Ali Basem Rebwar Nasir Dara Mohamed Shaban Sarminah Samad Raymond Ghandour Ahmad Almadhor Samah G. Babiker Iskandar Shernazarov Ibrahim A. Alsayer Waste heat recovery cycles integration into a net-Zero emission solar-thermal multi-generation system; Techno-economic analysis and ANN-MOPSO optimization Case Studies in Thermal Engineering Waste heat recovery Heat energy Solar-based system Fuel cell Multi-generation system Multi-objective optimization |
| title | Waste heat recovery cycles integration into a net-Zero emission solar-thermal multi-generation system; Techno-economic analysis and ANN-MOPSO optimization |
| title_full | Waste heat recovery cycles integration into a net-Zero emission solar-thermal multi-generation system; Techno-economic analysis and ANN-MOPSO optimization |
| title_fullStr | Waste heat recovery cycles integration into a net-Zero emission solar-thermal multi-generation system; Techno-economic analysis and ANN-MOPSO optimization |
| title_full_unstemmed | Waste heat recovery cycles integration into a net-Zero emission solar-thermal multi-generation system; Techno-economic analysis and ANN-MOPSO optimization |
| title_short | Waste heat recovery cycles integration into a net-Zero emission solar-thermal multi-generation system; Techno-economic analysis and ANN-MOPSO optimization |
| title_sort | waste heat recovery cycles integration into a net zero emission solar thermal multi generation system techno economic analysis and ann mopso optimization |
| topic | Waste heat recovery Heat energy Solar-based system Fuel cell Multi-generation system Multi-objective optimization |
| url | http://www.sciencedirect.com/science/article/pii/S2214157X24017210 |
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