Cost-Effective Flight Strategy for Aerial Thermography Inspection of Photovoltaic Power Plants

Abstract

Thermography from unmanned aerial vehicles (UAV) is widely used for module condition surveys and defect detection in solar (photovoltaic) power plants. This article presents an optimized defect inspection procedure in which a two-stage autonomous flight strategy is adopted to reduce the operation time, and thereby the cost. The first stage is a fast high-altitude flight for rapid coverage of the entire plant. The resolution on the modules is then somewhat degraded, but adequate for detection of possible defect locations. In the second stage, an optimized flight path is calculated to revisit and image only the detected locations from a lower altitude, where the resolution is sufficient for the classification of defects. This concept is studied through simulations of different plant geometries and defect densities. The simulations are supported by actual data, including a plant-scale survey. The proposed strategy is shown to have the potential for significant savings in operation time, on the order of 60% in the experimental case with 2% module defects. Commonly reported defect densities of 0.5% to 1% will give even larger savings. The inspection strategy is shown to be especially beneficial for plant geometries representative of high latitudes.