5 papers
Georeferencing of Photovoltaic Modules from Aerial Infrared Videos using Structure-from-Motion
Lukas Bommes, Claudia Buerhop-Lutz, Tobias Pickel +3
To identify abnormal photovoltaic (PV) modules in large-scale PV plants economically, drone-mounted infrared (IR) cameras and automated video processing algorithms are frequently u…
Module-Power Prediction from PL Measurements using Deep Learning
Mathis Hoffmann, Johannes Hepp, Bernd Doll +5
The individual causes for power loss of photovoltaic modules are investigated for quite some time. Recently, it has been shown that the power loss of a module is, for example, rela…
PV Modules and Their Backsheets -- A Case Study of a Multi-MW PV Power Station
Claudia Buerhop-Lutz, Oleksandr Stoyuk, Tobias Pickel +3
Degradation of backsheets (BS) and encapsulant polymer components of silicon PV modules is recognized as one of the main reasons for losses in PV plant performance and lifetime exp…
Deep Learning-based Pipeline for Module Power Prediction from EL Measurements
Mathis Hoffmann, Claudia Buerhop-Lutz, Luca Reeb +8
Automated inspection plays an important role in monitoring large-scale photovoltaic power plants. Commonly, electroluminescense measurements are used to identify various types of d…
Automatic Classification of Defective Photovoltaic Module Cells in Electroluminescence Images
Sergiu Deitsch, Vincent Christlein, Stephan Berger +4
Electroluminescence (EL) imaging is a useful modality for the inspection of photovoltaic (PV) modules. EL images provide high spatial resolution, which makes it possible to detect…