Fast and non-destructive quality control tools are important to assess the reliability of photovoltaic plants. On-site inspection is essential to minimize the risk of module damage and electrical yield losses. This may only be achieved by using highly sensitive imaging techniques such as luminescence or infrared thermography imaging. Nowadays, electroluminescence is used to detect defects such as local cell changes, series resistances and shunts in solar cells and modules which can cause electrical losses. However, the drawback of this method is the relatively low measurement throughput. To increase the throughput InGaAs cameras with a resolution of 640 × 512 pixels are used, for which low integration times are possible to acquire electroluminescence images. For such low integration times even moving image acquisition and movie recording are feasible to detect the mentioned defects. In this paper, an outdoor electroluminescence setup is presented for mobile handheld recording. Experiments showed that 5 ms integration time is a good compromise between low contrasts for lower integration times and motion blurring for higher integration times. The camera prototype has an onboard computer to avoid image transmission losses. It was controlled and visualized over Wi-Fi and remote desktop connection. The energy supply was provided from LiPo-batteries for improved mobility. In comparison to conventional electroluminescence measurements we can decrease the measurement time of a 20 module string from 5 min to 20 s.
Potential induced degradation (PID) causes severe damage and financial losses even in modern PV-installations. In Germany, approximately 19% of PV-installations suffer from PID and resulting power loss. This paper focuses on the impact of PID in real installations and how different evaluated time intervals influence the performance ratio (PR) and the determined degradation rate. The analysis focuses exemplarily on a 314 kWp PV-system in the Atlantic coastal climate. IR-imaging is used for identifying PID without operation interruption. Historic electric performance data are available from a monitoring system for several years on system level, string level as well as punctually measured module string IV- curves. The data sets are combined for understanding the PID behavior of this PV plant. The number of PID affected cells within a string varies strongly between 1 to 22% with the string position on the building complex. With increasing number of PID-affected cells the performance ratio decreases down to 60% for daily and monthly periods. Local differences in PID evolution rates are identified. An average PR-reduction of -3.65% per year is found for the PV-plant. On the string level the degradation rate varied up to 8.8% per year depending on the string position and the time period. The analysis reveals that PID generation and evolution in roof-top installations on industrial buildings with locally varying operation conditions can be fairly complex. The results yield that local operating conditions, e.g. ambient weather conditions as well as surrounding conditions on an industrial building, seem to have a dominating impact on the PID evolution rate.
First statistical evaluation of IR-inspections of PV-plants reveals that 86% of the installed PV-plants show IR-abnormalities. More than 120 PV-plants with more than 160,000 PV-modules were inspected and evaluated statistically. Main IR-abnormalities or failures in modules and string installations are analyzed, respectively. The average failure rate for PV-modules is about 8% and for module strings approximately 4%. The differentiation between the installation locations reveals that small residential installation show relatively more defective modules than large field installations. – Therefore, IR-imaging is a valuable method to give fast and reliable information about the actual quality and failure rate in inspected PV-installations.
Many PV-plants suffer from potential induced degradation (PID) which causes severe power reduction of installed PVmodules. Fast and reliable methods to detect PID and evaluate the impact on the module performance are gaining importance. Drone-assisted IR-inspection is a suitable method. PID affected modules are detected by their characteristic IR-fingerprint, modules with differing number of slightly heated cells occur more frequently at the negative string end. These modules show a degraded IV-curve, lowered Voc and Isc, and electroluminescence (EL)-images with suspicious, dark cells. Also, the measured string power is reduced. For a first quantitative data evaluation the suspicious cell are counted in the IR-images and correlated with the module power. A linear decrease of the module power with increasing number of suspicious cells results. A correlation function for estimating the module power was deduced, which has a mean deviation of less than 7%. This correlation function allows an acceptable approximation of the string power.
CIGS thin film solar modules, despite their high efficiency, may contain three different kinds of macroscopic defects referred to as bulk defects, interface defects and interconnect defects. These occur due to the film’s sensitivity to inhomogeneities during the manufacturing process and decreasing the electrical power output from a cell or module. In this study, we present infrared (IR) imaging and contactless loss analyses of defects contained in commercially manufactured thin film solar modules. We investigated different relations between the emitted IR-signal (using illuminated lock-in thermography ILIT) and the respective open circuit cell voltage (Voc) as well as the maximum power point (Pmpp). A simulation study, using the 2D finite element method (FEM), provides a deeper understanding as to the impact on electrical performance when defects are present on the cell or module.