Application of artificial neural networks for forecasting photovoltaic system parameters
- Авторлар: Miloudi L.1, Acheli D.1, Kesraoui M.1
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Мекемелер:
- University M’HamedBougara of Boumerdès
- Шығарылым: Том 53, № 2 (2017)
- Беттер: 85-91
- Бөлім: 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
Дәйексөз келтіру
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.
Авторлар туралы
Lalia Miloudi
University M’HamedBougara of Boumerdès
Хат алмасуға жауапты Автор.
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
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