Identify dusts on solar panels using drone still images

Abstract

These days electricity power is one among the basic needs of man. As the demand of electricity power is expanding, there is have to exploit renewable sources of energy. In the current period of power shortage in world, the utilization of solar energy could be helpful to great extent. Hence, the number and size of the Photovoltaic (PV) systems are developing and subsequently the amount of the investments and the related opportunities and risks are expanding To make solar energy progressively helpful, the effectiveness of solar power systems must be expanded. For the efficiency assessment of solar panels, that has been talked about with specific thoughtfulness regarding the presence of dust and maximum intensity of light on the solar panel surface. Essentially, the impacts of dusts and intensity of light on the efficiencies of solar panels have been highlighted. This paper gives the concise portrayal of the design and construction of dust identification of solar panels utilizing drone still images. It depends on the definition of an feature vector that characterizes portions of images that can be gained with a drone camera. The proposal has been applied to a lot of images taken in a operating solar panel power stations and the outcomes got exhibit its validity and robustness. Solar power station staff can without much of a stretch distinguish dusty solar panels utilizing this system. It will improve the output of power generation of solar power station and minimize manual work which doing by solar power station staff.