Application of artificial neural networks for forecasting photovoltaic system parameters
- Авторы: Miloudi L.1, Acheli D.1, Kesraoui M.1
-
Учреждения:
- University M’HamedBougara of Boumerdès
- Выпуск: Том 53, № 2 (2017)
- Страницы: 85-91
- Раздел: Direct Conversion of Solar Energy to Electricity
- URL: https://journals.rcsi.science/0003-701X/article/view/149271
- DOI: https://doi.org/10.3103/S0003701X17020104
- ID: 149271
Цитировать
Аннотация
The main element which justifies the installation of a photovoltaic system is the solar energy potential. Various structures of artificial neural networks (ANNs) are used for predicting the sun location, the global solar radiation (GSR) at horizontal and inclined plans. Real meteorological data have been exploited in order to validate the computation results. The ANNs are also carried out to predict the current-voltage characteristics of the photovoltaic module. It can be concluded that the ANNs effectively predict the behavior of photovoltaic system parameters with good a coefficient of determination.
Об авторах
Lalia Miloudi
University M’HamedBougara of Boumerdès
Автор, ответственный за переписку.
Email: lamiloudi@univ-boumerdes.dz
Алжир, Boumerdès
Dalila Acheli
University M’HamedBougara of Boumerdès
Email: lamiloudi@univ-boumerdes.dz
Алжир, Boumerdès
Mohamed Kesraoui
University M’HamedBougara of Boumerdès
Email: lamiloudi@univ-boumerdes.dz
Алжир, Boumerdès
Дополнительные файлы
