| Autor: |
Salleh, Nor Izzati Mohd, Nor, Ahmad Fateh Mohamad, Jumaat, Siti Amely, Yahaya, Jabbar Al-Fattah, Zainal, Nurezayana |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2023, Vol. 2564 Issue 1, p1-9, 9p |
| Abstrakt: |
Photovoltaic (PV) system is recognized as one of the most current renewable energy types in producing electricity power. However, one of the problems of PV system is that the performance of PV panel output is incompatible and affected due to changing climate condition. Hence, it is important to predict the actual generating output temperature of PV system. This study will cover up the implementation of PV system at the rooftop of Mega label SDN.BHD with type of poly-crystalline 405.72KWP as use for generate electricity for production purpose and to get Module temperature as actual measurement. Then, the optimal PV output temperature on the rooftop which is module temperature predict the comparison data with simple mathematical method and Artificial Neural Network (ANN). To produce ANN values then, custom MLPBP ANN network and generate in MATLAB. The results have shown that ANN has the ability to predict the PV output close to the module temperature which is the actual measurement compared to mathematical method. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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