Electro-Thermal Modeling of Soiled Photovoltaic Modules

Abstract

Solar energy plays a major role in the transition to renewable energy. To ensure that large-scale photovoltaic (PV) power plants operate at their full potential, monitoring them is essential. It is common practice to utilize drones equipped with Infrared Thermography (IRT) cameras to detect defects in modules, as they lead to deviating thermal behavior. However, IRT images also show temperature hotspots for inhomogeneous soiling on the module’s surface. Hence, the method does not differentiate between defective and soiled modules, which may cause false identification and economic and resource loss when replacing soiled but intact modules. To avoid this, the DLR proposes to also capture aerial images with ordinary cameras during the flights. These images can be used to identify soiling losses. This thesis presents an electro-thermal model that translates the soiling losses of PV modules into high-resolution temperature maps. By comparing temperature maps with IRT images, it can be determined whether the module is soiled or defective. The proposed solution consists of an electrical model and a thermal model which influence each other. The electrical model replicates the power output of each cell, whereas the thermal model calculates the individual cell temperatures. Both models consider the given soiling and weather conditions. To evaluate the model performance, we conducted on-site experiments at CIEMAT’s solar technology research center PSA in Almería, Spain. Our results show that inhomogeneous soiling forms temperature hotspots which are well recognizable in the simulated temperature maps. The model also predicts valid cell temperatures for clean cells and soiled strings. Furthermore, we found that the electro-thermal model predicts power losses for different soiling conditions with consistent accuracy.