Photovoltaic panel dusting early warning method and device, electronic equipment and storage medium

Abstract

The application discloses a dust accumulation early warning method and device for a photovoltaic panel, electronic equipment and a storage medium. A multispectral synchronous acquisition mode covering ultraviolet, visible light and near-infrared is adopted to capture the differentiated attenuation characteristics of dust of different particle sizes and components on each waveband. In combination with environmental light differential compensation, interference such as sunshine fluctuation and cloud cover is eliminated, and the risk of misjudgment is reduced from the source. By constructing an attenuation rate ratio matrix to quantify the relative deviation degree of multiple wavebands, dust accumulation and condensation, sudden changes in illumination and other different scenarios are distinguished, and false alarms and missed detections caused by a single light intensity signal are avoided. By fusing historical spectral statistical characteristics, real-time environmental parameters and seasonal climate patterns, a dust accumulation early warning threshold is generated by using a machine learning model, and the problem of poor adaptability of a fixed threshold in different seasons and environments is overcome. The technical effects of significantly reducing the false alarm rate and the missed detection rate, accurately identifying dust accumulation distribution and material composition, optimizing cleaning resource scheduling and improving the long-term power generation efficiency and safety and stability of a photovoltaic power station are achieved.

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