earticle

영어

The accumulation of dust on the solar panels causes a significant decrease in the efficiency of the panels, particularly in dry and semi-arid climates, where the energy yield is affected. This paper discusses how the VGG16 DL model can be applied to the real-time detection of dust that covers the solar panel to enhance their maintenance and improve energy efficiency. Using the VGG16, pre-trained on large image datasets, fine-tune this model to classify between clean and dusty solar panels. The model is thus trained on a holistic dataset of solar panels with variation under different environmental conditions. This approach minimizes energy loss, reduces keep costs, and enhances and overall performance and lifespan of solar panels. The method holds considerable promise for solar farms to optimize cleaning schedules and maximize energy production, promoting more sustainable solar energy solutions.