Fault Detection and Power Loss Assessment for Rooftop Photovoltaics Installed in a University Campus, by Use of UAV-Based Infrared Thermography

In contrast to commercial photovoltaic (PV) power plants, PV systems at universities are not actively monitored for PV module failures, which can result in a loss of power generation. In this study, we used thermal imaging with drones to detect rooftop PV module failures at a university campus before comparing reductions in power generation according to the percentage of module failures in each building. Toward this aim, we adjusted the four factors affecting the power generation of the four buildings to have the same values (capacities, degradations due to aging, and the tilts and orientation angles of the PV systems) and calibrated the actual monthly power generation accordingly. Consequently, we detected three types of faults, namely open short-circuits, hot spots, and potential-induced degradation. Furthermore, we found that the higher the percentage of defective modules, the lower the power generation. In particular, the annual power generation of the building with the highest percentage of defective modules (12%) was reduced by approximately 25,042 kWh (32%) compared to the building with the lowest percentage of defective modules (4%). The results of this study can contribute to improving awareness of the importance of detecting and maintaining defective PV modules on university campuses and provide a useful basis for securing the sustainability of green campuses.