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...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-01-01
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| Series: | Solar Energy Advances |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S266711312500021X |
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