Scientific publication

Diagnosing PID in Field Electroluminescence Inspections of PV Modules Using Multilevel Forward Current Biasing

Oct 1, 2025

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 quantify relative changes in luminescence between degraded cells and a reference cell within the same module by acquiring EL images at two distinct current injection levels. The resulting metric enables automatic PID characterization and reduces reliance on subjective visual interpretation. The approach was further adapted for daylight field EL inspections using a multibias modulation technique, which introduces an intermediate current bias between high-current injection and open-circuit voltage (Voc). This adaptation mitigates variability from changing irradiance, allowing effective PID characterization under low irradiance conditions. Validation in both field and lab environments confirmed the robustness of the method, with module luminescence differences exceeding 2.5% even at 50% current bias. These results highlight the potential of the proposed metric for reliable PID diagnosis in PV modules.

Influence of irradiance and drone altitude in infrared thermography inspections of photovoltaic plants

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...

Influence of irradiance and drone altitude in infrared thermography inspections of photovoltaic plants

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...

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