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Title:
Machine learning-based fault detection technique for bifacial PV
Detail:
A UAE research team developed a hybrid 1D-CNN and random forest model to detect multiple faults in bifacial PV systems, including dust, shading, aging, and cracks. Using simulated I-V curves and a 180-day synthetic dataset, the model achieved up to 100% accuracy in general state detection and 97.6% in specific fault classification.
Country:
International
Source:
PV-Magazine
Published Date:
22.10.2025
URL:
View Original URL
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Regions:
Africa Asia Australia Europe North America Oceania South America
Sectors:
Infrastructure Construction Energy-Power and Electrical Computer Hardwares and Consumables
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