Presentation Description: Solar photovoltaic (PV) modules are known to degrade over time due to various factors such as environmental stresses, manufacturing defects, and module design. Electroluminescence (EL) imaging is a non-destructive imaging technique widely used to diagnose the degradation in solar PV modules. This poster showcases the machine learning tool’s ability to identify solar PV module defects. These images are captured using the principles of EL imaging. We also present different defects commonly found in EL images and their impact on the characterization of the longevity of the PV module. Finally, we discuss the challenges and prospects of our tool in the solar PV industry.
Learning Objectives:
Upon completion, the participant will be able to list different PV module defects that are detected through EL imaging analysis
Upon completion, the participant will be able to describe different applications of the EL imaging in the solar industry
Upon completion, the participant will be able to understand how EL imaging can help warranty and repair process
