Numerical Evaluation and Artificial Neural Network (ANN) Model of the Photovoltaic Thermal (PVT) System with Different Nanofluids
The present study investigates the performance of photovoltaic thermal (PVT) systems that employ silver, aluminum oxide, copper, and titanium dioxide nanoparticles with distilled water as a solvent. The volume portions of the nanoparticles considered are 2% and 5% by weight. The study employs an ene...
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | International Journal of Photoenergy |
| Online Access: | http://dx.doi.org/10.1155/2024/6649100 |
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| author | Mrigendra Singh S. C. Solanki Basant Agrawal Rajesh Bhargava |
| author_facet | Mrigendra Singh S. C. Solanki Basant Agrawal Rajesh Bhargava |
| author_sort | Mrigendra Singh |
| collection | DOAJ |
| description | The present study investigates the performance of photovoltaic thermal (PVT) systems that employ silver, aluminum oxide, copper, and titanium dioxide nanoparticles with distilled water as a solvent. The volume portions of the nanoparticles considered are 2% and 5% by weight. The study employs an energy balance equation to encompass circular geometries for fluid flow channels and a flow velocity ranging from 1×10−4 to 3×10−4 m/s. A numerical model has been established to investigate the performance of the photovoltaic thermal system and obtained the highest performance in Cu/water nanofluid for a uniform mass flow rate of 0.0670 kg/s and volume portion of 5% compared to other nanofluids, and the average electrical, thermal, and overall performance achieved is 15.8%, 30.2%, and 45.3%, respectively. Moreover, an artificial neural network (ANN) was developed to predict the electrical and thermal efficiency of the PVT system, and the mean absolute percentage error (MAPE) between array error of the thermal and electrical efficiency of the system is 4.98% and 2.61%, respectively. This value shows the strong validation of the numerical and ANN simulation values. |
| format | Article |
| id | doaj-art-5e8076e7826b4a55a72711d5fdbaade7 |
| institution | OA Journals |
| issn | 1687-529X |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Photoenergy |
| spelling | doaj-art-5e8076e7826b4a55a72711d5fdbaade72025-08-20T02:05:08ZengWileyInternational Journal of Photoenergy1687-529X2024-01-01202410.1155/2024/6649100Numerical Evaluation and Artificial Neural Network (ANN) Model of the Photovoltaic Thermal (PVT) System with Different NanofluidsMrigendra Singh0S. C. Solanki1Basant Agrawal2Rajesh Bhargava3Department of Mechanical EngineeringDepartment of Mechanical EngineeringDepartment of Mechanical EngineeringRGPV BhopalThe present study investigates the performance of photovoltaic thermal (PVT) systems that employ silver, aluminum oxide, copper, and titanium dioxide nanoparticles with distilled water as a solvent. The volume portions of the nanoparticles considered are 2% and 5% by weight. The study employs an energy balance equation to encompass circular geometries for fluid flow channels and a flow velocity ranging from 1×10−4 to 3×10−4 m/s. A numerical model has been established to investigate the performance of the photovoltaic thermal system and obtained the highest performance in Cu/water nanofluid for a uniform mass flow rate of 0.0670 kg/s and volume portion of 5% compared to other nanofluids, and the average electrical, thermal, and overall performance achieved is 15.8%, 30.2%, and 45.3%, respectively. Moreover, an artificial neural network (ANN) was developed to predict the electrical and thermal efficiency of the PVT system, and the mean absolute percentage error (MAPE) between array error of the thermal and electrical efficiency of the system is 4.98% and 2.61%, respectively. This value shows the strong validation of the numerical and ANN simulation values.http://dx.doi.org/10.1155/2024/6649100 |
| spellingShingle | Mrigendra Singh S. C. Solanki Basant Agrawal Rajesh Bhargava Numerical Evaluation and Artificial Neural Network (ANN) Model of the Photovoltaic Thermal (PVT) System with Different Nanofluids International Journal of Photoenergy |
| title | Numerical Evaluation and Artificial Neural Network (ANN) Model of the Photovoltaic Thermal (PVT) System with Different Nanofluids |
| title_full | Numerical Evaluation and Artificial Neural Network (ANN) Model of the Photovoltaic Thermal (PVT) System with Different Nanofluids |
| title_fullStr | Numerical Evaluation and Artificial Neural Network (ANN) Model of the Photovoltaic Thermal (PVT) System with Different Nanofluids |
| title_full_unstemmed | Numerical Evaluation and Artificial Neural Network (ANN) Model of the Photovoltaic Thermal (PVT) System with Different Nanofluids |
| title_short | Numerical Evaluation and Artificial Neural Network (ANN) Model of the Photovoltaic Thermal (PVT) System with Different Nanofluids |
| title_sort | numerical evaluation and artificial neural network ann model of the photovoltaic thermal pvt system with different nanofluids |
| url | http://dx.doi.org/10.1155/2024/6649100 |
| work_keys_str_mv | AT mrigendrasingh numericalevaluationandartificialneuralnetworkannmodelofthephotovoltaicthermalpvtsystemwithdifferentnanofluids AT scsolanki numericalevaluationandartificialneuralnetworkannmodelofthephotovoltaicthermalpvtsystemwithdifferentnanofluids AT basantagrawal numericalevaluationandartificialneuralnetworkannmodelofthephotovoltaicthermalpvtsystemwithdifferentnanofluids AT rajeshbhargava numericalevaluationandartificialneuralnetworkannmodelofthephotovoltaicthermalpvtsystemwithdifferentnanofluids |