SCIENTIFIC PUBLICATIONS
Discover the scientific publications of the SOLARIS project.
Influence of irradiance and drone altitude in infrared thermography inspections of photovoltaic plants
This study evaluates the effectiveness of drone-based infrared thermography (IRT) for detecting photovoltaic (PV) module defects under varying drone altitudes and irradiance levels. A total of 43 PV modules were artificially degraded to induce common faults, including cell cracks, potential-induced degradation (PID), cell interconnect disconnections, glass cracks, and short-circuited bypass...
What is the Optimal Path for a Drone Exploring a PV Plant?
Inspecting photovoltaic (PV) plants is essential to ensure optimal performance. Drones can be employed to acquire both optical and thermal data for anomaly detection. However, while visual servoing can accurately guide a drone along individual PV panel rows, the inter-panel transitions between subsequent rows rely on the Global Navigation Satellite...
Diagnosing PID in Field Electroluminescence Inspections of PV Modules Using Multilevel Forward Current Biasing
Potential-induced degradation (PID) in photovoltaic (PV) modules can be identified using electroluminescence (EL) imaging by comparing the luminescence of degraded cells to that of healthy cells. In nondegraded modules, cells exhibit consistent radiative recombination and luminescence properties, whereas PID alters these, creating measurable differences. This work presents a methodology to...
Evaluating IV curve derived features for fault detection
IV curves contain diagnostic information which characterizes faults in photovoltaic systems. Past research used IV curve derived features for fault detection, but a systematic investigation of features in outdoor conditions is missing. In this work, we perform outdoor IV measurements on module level with varying penetration of potential induced degradation,...
Benchmarking Power Loss Simulation Models for Cracked Photovoltaic Cells Using Electroluminescence Images: The Effect of Daylight and Image Resolution
Algorithms and models for simulating power loss in photovoltaic (PV) cells using electroluminescence (EL) images are typically developed, trained, and validated on high-resolution images acquired under dark laboratory conditions. In this work we benchmark the performance of an analytical model (bELMO) and a data-driven power loss simulation model (DTU ML)...