Machine learning - driven solar forecasting in dust-prone regions for sustainable energy systems

This research focuses on improving solar energy forecasting in dust-affected regions such as the UAE, where frequent dust storms reduce photovoltaic (PV) efficiency by scattering and absorbing sunlight. Many existing models overlook the impact of dust events, leading to inaccurate forecasts during s...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Kadhim Hayawi, Husna Maliakkal, Neethu Venugopal, Thanveer Musthafa Hussain, Gomathi Bhavani Rajagopalan
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	Elsevier 2025-01-01
Sarja:	Solar Energy Advances
Aiheet:	Sustainable energy Solar energy forecasting Dust impact Photovoltaic (PV) efficiency Machine learning
Linkit:	http://www.sciencedirect.com/science/article/pii/S266711312500021X
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