Thermal Infrared and Visual Inspection of Photovoltaic Installations by UAV Photogrammetry—Application Case: Morocco

Abstract

Being sustainable, clean, and eco-friendly, photovoltaic technology is considered as one of the most hoped solutions face to worldwide energetic challenges. Morocco joins this context with the inauguration of numerous clean energy projects. However, one key factor in making photovoltaic installations a profitable investment are regular and effective inspections in order to detect occurred defects. Unmanned aerial vehicles (UAV) are increasingly used in various inspection fields. In this respect, this work focuses on the use of thermal and visual imagery taken by UAV in the inspection of photovoltaic installations. Visual and thermal images of photovoltaic modules, obtained by UAV, from different installations, and with different acquisition conditions and parameters, were exploited to generate orthomosaics for inspection purposes. The methodology was tested on a dataset we have acquired by a mission in Rabat (Morocco), and also on external datasets acquired in Switzerland. As final results, several visual defects were detected in visual RGB and thermal orthomosaics, such as cracks, soiling, and hotspots. In addition, a procedure of semi-automatic hotspots’ extraction was also developed and is presented within this work. On the other side, various tests were conducted on the influence of some acquisition and processing parameters (images’ overlap, the ground sampling distance, the flying height, the use of ground control points, the internal camera parameters’ optimization) on the detection of defects and the quality of visual and thermal generated orthomosaics. In the end, the potential of UAV thermal and visual imagery in the inspection of photovoltaic installations was discussed in function of various parameters. On the basis of the discussion feedback, UAV were concluded as advantageous tools within the thematic of this project, which proves the necessity of their implementation in this context.