A novel image enhancement algorithm to determine the dust level on photovoltaic (PV) panels

Abstract

An accurate evaluation of the dust accumulation on photovoltaic (PV) panels enables the development of cleaning plans and improves the grid connection security of PV power stations. In this paper, a novel image enhancement algorithm is proposed to evaluate the dust accumulation on PV panels. An atmospheric scattering model was used to analyze the difference in the image characteristics of clean and dusty PV panels. A model was proposed to describe the relationship between the model coefficient and the dust level by minimizing the pixel difference between the images of the soiled and clean PV panels. An experiment system was designed to acquire the images of clean and soiled PV panels with different dust levels. The model parameters were determined by data fitting, and the model’s generalization ability was improved by adding a noise item. The results show that the model can estimate the dust level on PV panels with an accuracy of 83.78%. The average root mean square error (RMSE) of samples 1–4 is 1.67, and the error range is 2–3.5 g/m2. In addition, the proposed method has higher accuracy than the optical attenuation and weighing methods, with a mean absolute error (MAE) of 1.61 g/m2. The method is simple and reliable for intelligent cleaning of PV panels.