In recent years, there has been a lot of interest in clean energy especially in solar energy leading to the construction of numerous photovoltaic (PV) panels around the world. These panels need to be inspected to make sure they produce the desired amount of electricity. There are many methods to inspect which are manual, semi-autonomous and fully autonomous. The manual and semi-autonomous already exist but the process is tedious and requires a lot of time and resources. In this paper, we propose a fully autonomous solution where the drone will be preprogrammed to follow certain waypoints inputted via GPS data. The drone is equipped with a thermal camera where the video is recorded for postprocessing. The video is processed offline in order to detect the panels using image processing techniques such as thresholding, binary, canny edge, hough transform, and others. The novelty of this paper is on proposing a fully integrated solution for PV panel detection using a drone; it paves a way for future applications involving machine and deep learning.