Using Image Analysis Techniques for Dust Detection Over Photovoltaic Panels

It is widely known that photovoltaic technology has been massively distributed over the last decade despite its low-efficiency ratio. Dust deposition reduces this efficiency even more lowering the energy production and reducing module performance. In this work, we developed an artificial vision algorithm based on CIELAB color space to identify dust over panels in an automatic way. The proposed algorithm uses a series of images of soiled panels and creates a simulation with a known soiling coefficient to compare with the real ones. All the images were taken directly by drones or cellphone cameras. The results prove satisfactory with a maximum error of approximately 4.14% with respect to visual inspection and a resolution of 4.4%. The algorithm is independent of training and uses the soiling over the panel to create the simulation so that it could be valid at any location.