## 1 Introduction  
According to the International Energy Agency (IEA), photovoltaic (PV) power generation accounted for 5.4% of global electricity demand in 2023 [1]. Moreover, PV technology is expected to become the largest renewable energy source by 2029, surpassing wind and hydropower [1]. Proper operation and maintenance of PV power plants requires inspection techniques for PV modules [2, 3, 4, 5], which are considered the most vulnerable components of any PV plant to faults, as they are exposed to various environmental stressors such as hail, moisture or ultraviolet (UV) radiation. The implementation of inspection techniques enables the detection of faults and anomalies, improving PV power plant operation, reducing safety risks and maximizing energy output [2; 3; 6]. Inspection techniques can be categorized into electrical measurements and imaging techniques. Current-Voltage (I-V) curve analysis is the primary electrical measurement performed in PV power plants [3], providing quantitative data that can be compared to manufacturer specifications for fault detection and degradation analysis [3]. While I-V curve measurements require system disconnection and can be time-consuming, imaging techniques offer the potential to inspect multiple modules in a shorter time, making them a cost-effective tool for fault detection [3], particularly when unmanned aerial vehicles (UAVs) are used [3; 7]. Common imaging techniques include thermography and luminescence inspections [3]. Thermography is widely used in utility-scale PV power plants, as thermal cameras can be easily integrated into UAVs, enabling fast and cost-effective inspections during normal operation of the power plant [8; 9]. Luminescence imaging has also gained popularity in recent years, as it can detect a broader range of faults compared to infrared imaging due to its higher spatial resolution [10; 11]. However, outdoor luminescence measurements are more challenging, which limits their applicability for field inspections. Luminescence imaging is based on capturing the emission generated by solar cells when exposed to different energy sources. Luminescence emission can be induced either by electrical excitation, where a current is injected into the PV device, known as electroluminescence (EL), or by illuminating the PV device with an appropriate light source, referred to as photoluminescence (PL). Both EL and PL imaging can detect a wide range of failures and anomalies in solar cells, including delamination, potential-induced degradation, cracks, cell inhomogeneities, corrosion, diode faults and soldering issues, among others [10; 12; 13]. For silicon solar cells, the peak luminescence emission wavelength is 1150 nm [14]. In contrast, Cadmium Telluride (CdTe) solar cells exhibit a luminescence peak around 800 nm [15]. Regarding silicon technology, two types of sensors are suitable for luminescence applications: silicon and Indium Gallium Arsenide (InGaAs) sensors [10; 16]. Silicon sensors are more affordable and offer high resolution, but their low sensitivity to luminescence emission requires long exposure times and a dark environment. Meanwhile, InGaAs sensors have a sensitivity that closely matches the luminescence emission of silicon solar cells, making them suitable for measurements under high irradiance conditions and short exposure times, although they are more expensive and have lower resolution. Conventional luminescence measurements have traditionally been performed at night, using power supplies as excitation sources to achieve the EL effect by injecting current [10; 12], typically around the module's short-circuit current. The need for nighttime measurements, module disconnection and external power supplies limits the applicability of this technique. In recent years, several approaches have been proposed to overcome the limitations of conventional luminescence imaging techniques.