Maximizing photovoltaic thermal system through computational fluid dynamics-driven multi-factor parametric optimization: A Taguchi-grey relational analysis method to enhancing electrical output and cooling efficiency for sustainable energy
This study presents a computational fluid dynamics (CFD)-based grey relational analysis (GRA) using the Taguchi method for the parametric optimisation of a photovoltaic thermal (PVT) system. The objective of the study is to use the excess thermal energy to increase the amount of electricity produced...
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Elsevier
2025-05-01
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| Series: | Case Studies in Thermal Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X25002515 |
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| author | Natnale Sitotaw Asefa Kiran Shahapurkar Tilahun Nigussie Abdulkadir Aman Hassen Manzoore Elahi M. Soudagar Yasser Fouad Irfan Ali Sagar Shelare Shubham Sharma V.K. Bupesh Raja Abinash Mahapatro Sarabjit Singh Abhinav Kumar Ehab El Sayed Massoud Jasmina Lozanovic |
| author_facet | Natnale Sitotaw Asefa Kiran Shahapurkar Tilahun Nigussie Abdulkadir Aman Hassen Manzoore Elahi M. Soudagar Yasser Fouad Irfan Ali Sagar Shelare Shubham Sharma V.K. Bupesh Raja Abinash Mahapatro Sarabjit Singh Abhinav Kumar Ehab El Sayed Massoud Jasmina Lozanovic |
| author_sort | Natnale Sitotaw Asefa |
| collection | DOAJ |
| description | This study presents a computational fluid dynamics (CFD)-based grey relational analysis (GRA) using the Taguchi method for the parametric optimisation of a photovoltaic thermal (PVT) system. The objective of the study is to use the excess thermal energy to increase the amount of electricity produced by the PV systems. This study is distinguished by design factors such as tube configuration and geometry, operational conditions including mass flow rate and fluid inlet temperature, and external environmental parameters including ambient temperature and solar irradiation. This study employs a distinctive integration of CFD simulations with Grey Relational Analysis (GRA) to optimise photovoltaic thermal (PV/T) systems via multi-factor analysis. This approach optimises electrical and thermal efficiency, tackling essential performance compromises overlooked by traditional methods. This strategy enhances system efficiency and guides the design of modern, sustainable PVT systems. The research additionally highlights the need of mitigating hotspots in the photovoltaic panel and increasing the temperature of the cooling water outlet. The results indicate the significant impact of multiple factors on the GRA analysis of variance: flow pattern (6.52 %), tube area (0.53 %), mass flow rate (15.68 %), ambient temperature (4.42 %), and radiation (42.27 %). The Taguchi projected optimal configuration (A1B3C3D3E3F1) attained a GRG of 0.791, which closely corresponds with the simulated GRG of 0.752, thus illustrating the trustworthiness of the predictive model. Furthermore, the PV thermal system exhibited a significant improvement in multi-factor performance. The system attained a 16.19 % enhancement in thermal efficiency, a 17.34 % decrease in PV mean variation (indicating substantial hotspot mitigation), and a large temperature output increase of 7.99 °C. These enhancements highlight the system's ingenuity and its capacity to elevate photovoltaic thermal efficacy. This unique work integrates CFD simulations with Grey Relational Analysis (GRA) and the Taguchi technique to create a multi-objective optimisation strategy that properly forecasts the most important PVT system performance parameters. Results show great computational precision (uncertainty <10−4) and 95.1 % agreement between predicted and simulated results, offering a reliable foundation for optimising PVT system thermal and electrical efficiency. |
| format | Article |
| id | doaj-art-3232b87f53874fefb5e297474e23da34 |
| institution | OA Journals |
| issn | 2214-157X |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Case Studies in Thermal Engineering |
| spelling | doaj-art-3232b87f53874fefb5e297474e23da342025-08-20T02:17:28ZengElsevierCase Studies in Thermal Engineering2214-157X2025-05-016910599110.1016/j.csite.2025.105991Maximizing photovoltaic thermal system through computational fluid dynamics-driven multi-factor parametric optimization: A Taguchi-grey relational analysis method to enhancing electrical output and cooling efficiency for sustainable energyNatnale Sitotaw Asefa0Kiran Shahapurkar1Tilahun Nigussie2Abdulkadir Aman Hassen3Manzoore Elahi M. Soudagar4Yasser Fouad5Irfan Ali6Sagar Shelare7Shubham Sharma8V.K. Bupesh Raja9Abinash Mahapatro10Sarabjit Singh11Abhinav Kumar12Ehab El Sayed Massoud13Jasmina Lozanovic14School of Mechanical and Industrial Engineering, Addis Ababa Institute of Technology, Addis Ababa University, Addis Ababa, Ethiopia; Corresponding author.Centre of Molecular Medicine and Diagnostics (COMManD), Saveetha Dental College and Hospitals Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, 600 077, IndiaSchool of Mechanical and Industrial Engineering, Addis Ababa Institute of Technology, Addis Ababa University, Addis Ababa, EthiopiaSchool of Mechanical and Industrial Engineering, Addis Ababa Institute of Technology, Addis Ababa University, Addis Ababa, EthiopiaChitkara Centre for Research and Development, Chitkara University, Himachal Pradesh, 174103, India; College of Engineering, Lishui University, Zhejiang, Lishui, 323000, China; Corresponding author. Department of Mechanical Engineering, Graphic Era (Deemed to be University), Dehradun, Uttarakhand, 248002, India.Department of Applied Mechanical Engineering, College of Applied Engineering, Muzahimiyah Branch, King Saud University, P.O. Box 800, 11421, Riyadh, Saudi ArabiaDepartment of Mechanical Engineering, Adama Science and Technology University, EthiopiaDepartment of Mechanical Engineering, Priyadarshini College of Engineering, Nagpur, 440019, Maharashtra, IndiaDepartment of Technical Sciences, Western Caspian University, Baku, Azerbaijan; Centre for Research Impact and Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, 140401, Punjab, IndiaDepartment of Mechanical Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, IndiaDepartment of Mechanical Engineering, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, Odisha, 751030, IndiaDepartment of Mechanical Engineering, Chandigarh Engineering College, Chandigarh Group of Colleges-Jhanjeri, Mohali, Punjab, 140307, IndiaDepartment of Nuclear and Renewable Energy, Ural Federal University Named After the First President of Russia, Boris Yeltsin, 19 Mira Street, 620002, Ekaterinburg, RussiaCollege of Applied Sciences, Dhahran Al-Janoub, King Khalid University, Kingdom of Saudi ArabiaUniversity of Applied Sciences Campus Vienna, Department of Engineering, 1100, Vienna, Austria; Corresponding author.This study presents a computational fluid dynamics (CFD)-based grey relational analysis (GRA) using the Taguchi method for the parametric optimisation of a photovoltaic thermal (PVT) system. The objective of the study is to use the excess thermal energy to increase the amount of electricity produced by the PV systems. This study is distinguished by design factors such as tube configuration and geometry, operational conditions including mass flow rate and fluid inlet temperature, and external environmental parameters including ambient temperature and solar irradiation. This study employs a distinctive integration of CFD simulations with Grey Relational Analysis (GRA) to optimise photovoltaic thermal (PV/T) systems via multi-factor analysis. This approach optimises electrical and thermal efficiency, tackling essential performance compromises overlooked by traditional methods. This strategy enhances system efficiency and guides the design of modern, sustainable PVT systems. The research additionally highlights the need of mitigating hotspots in the photovoltaic panel and increasing the temperature of the cooling water outlet. The results indicate the significant impact of multiple factors on the GRA analysis of variance: flow pattern (6.52 %), tube area (0.53 %), mass flow rate (15.68 %), ambient temperature (4.42 %), and radiation (42.27 %). The Taguchi projected optimal configuration (A1B3C3D3E3F1) attained a GRG of 0.791, which closely corresponds with the simulated GRG of 0.752, thus illustrating the trustworthiness of the predictive model. Furthermore, the PV thermal system exhibited a significant improvement in multi-factor performance. The system attained a 16.19 % enhancement in thermal efficiency, a 17.34 % decrease in PV mean variation (indicating substantial hotspot mitigation), and a large temperature output increase of 7.99 °C. These enhancements highlight the system's ingenuity and its capacity to elevate photovoltaic thermal efficacy. This unique work integrates CFD simulations with Grey Relational Analysis (GRA) and the Taguchi technique to create a multi-objective optimisation strategy that properly forecasts the most important PVT system performance parameters. Results show great computational precision (uncertainty <10−4) and 95.1 % agreement between predicted and simulated results, offering a reliable foundation for optimising PVT system thermal and electrical efficiency.http://www.sciencedirect.com/science/article/pii/S2214157X25002515CFDPhotovoltaicPercentage contributionGRASolar radiation |
| spellingShingle | Natnale Sitotaw Asefa Kiran Shahapurkar Tilahun Nigussie Abdulkadir Aman Hassen Manzoore Elahi M. Soudagar Yasser Fouad Irfan Ali Sagar Shelare Shubham Sharma V.K. Bupesh Raja Abinash Mahapatro Sarabjit Singh Abhinav Kumar Ehab El Sayed Massoud Jasmina Lozanovic Maximizing photovoltaic thermal system through computational fluid dynamics-driven multi-factor parametric optimization: A Taguchi-grey relational analysis method to enhancing electrical output and cooling efficiency for sustainable energy Case Studies in Thermal Engineering CFD Photovoltaic Percentage contribution GRA Solar radiation |
| title | Maximizing photovoltaic thermal system through computational fluid dynamics-driven multi-factor parametric optimization: A Taguchi-grey relational analysis method to enhancing electrical output and cooling efficiency for sustainable energy |
| title_full | Maximizing photovoltaic thermal system through computational fluid dynamics-driven multi-factor parametric optimization: A Taguchi-grey relational analysis method to enhancing electrical output and cooling efficiency for sustainable energy |
| title_fullStr | Maximizing photovoltaic thermal system through computational fluid dynamics-driven multi-factor parametric optimization: A Taguchi-grey relational analysis method to enhancing electrical output and cooling efficiency for sustainable energy |
| title_full_unstemmed | Maximizing photovoltaic thermal system through computational fluid dynamics-driven multi-factor parametric optimization: A Taguchi-grey relational analysis method to enhancing electrical output and cooling efficiency for sustainable energy |
| title_short | Maximizing photovoltaic thermal system through computational fluid dynamics-driven multi-factor parametric optimization: A Taguchi-grey relational analysis method to enhancing electrical output and cooling efficiency for sustainable energy |
| title_sort | maximizing photovoltaic thermal system through computational fluid dynamics driven multi factor parametric optimization a taguchi grey relational analysis method to enhancing electrical output and cooling efficiency for sustainable energy |
| topic | CFD Photovoltaic Percentage contribution GRA Solar radiation |
| url | http://www.sciencedirect.com/science/article/pii/S2214157X25002515 |
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