Validation Study Of Photovoltaic Thermal Nanofluid Based Coolant Using Computational Fluid Dynamics Approach
In the study, the photovoltaic thermal system using nanofluid as coolant is validated using numerical approach by comparing the experimental results and simulation results. Due to high cost and difficulty in preparing nanofluid, it is more practical to perform the study using numerical approach whic...
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| Main Authors: | , , , , , , , , |
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| 格式: | Article |
| 語言: | English |
| 出版: |
Penerbit Akademia Baru
2021
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| 在線閱讀: | http://eprints.utem.edu.my/id/eprint/25643/2/2945-MANUSCRIPT%20WITH%20AUTHORS%20DETAILS-16986-1-10-20210331.PDF http://eprints.utem.edu.my/id/eprint/25643/ https://www.akademiabaru.com/submit/index.php/cfdl/article/view/2945/2749 https://doi.org/10.37934/cfdl.13.3.5871 |
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| 總結: | In the study, the photovoltaic thermal system using nanofluid as coolant is validated using numerical approach by comparing the experimental results and simulation results. Due to high cost and difficulty in preparing nanofluid, it is more practical to perform the study using numerical approach which is convenient and saves plenty of time. The photovoltaic thermal system is investigated numerically through Computational Fluid Dynamics Approach using Ansys 19.0 Fluent Software. The numerical study is based on different solar irradiation at different hours. The coolant that is selected in the study is aluminum oxide (Al2O3) water nanofluid. The validation study between the experimental results and simulation results are achieved by examining the photovoltaic (PV) surface temperature and nanofluid outlet temperature. The maximum percentage of error between experimental and simulation
results of PV surface temperature and nanofluid outlet temperature are 12.66% and 7.89%. Also, the mean average percentage error (MAPE) are computed for PV surface temperature and nanofluid outlet temperature. The results for PV surface temperature and nanofluid outlet temperature are 10.31% and 6.67%. Since the MAPE results are within 10% or error, it proved that there are good accuracy between the simulation and experimental results |
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