We show that accurate sheet resistance measurements on small samples may be performed using microfour-point probes without applying correction factors. Using dual configuration measurements, the sheet resistance may be extracted with high accuracy when the microfour-point probes are in proximity of a mirror plane on small samples with dimensions of a few times the probe pitch. We calculate theoretically the size of the "sweet spot," where sufficiently accurate sheet resistances result and show that even for very small samples it is feasible to do correction free extraction of the sheet resistance with sufficient accuracy. As an example, the sheet resistance of a 40 m ͑50 m͒ square sample may be characterized with an accuracy of 0.3% ͑0.1%͒ using a 10 m pitch microfour-point probe and assuming a probe alignment accuracy of Ϯ2.5 m.

Electroluminescence (EL) imaging is a PV module characterization technique, which provides high accuracy in detecting defects and faults such as cracks, broken cells interconnections, shunts, among many others; furthermore, the EL technique is used extensively due to a high level of detail and direct relationship to injected carrier density. However, this technique is commonly practiced only indoors-or outdoors from dusk to dawn-because the crystalline silicon luminescence signal is several orders of magnitude lower than sunlight. This limits the potential of such a powerful technique to be used in utility scale inspections, and therefore the interest in the development of electrical biasing tools to make outdoor EL imaging truly fast and efficient. With the focus of quickly acquiring EL images in daylight, we present in this article a drone-based system capable of acquiring EL images at a framerate of 120 frames per second. In a single second during high irradiance conditions, this system can capture enough EL and background image pairs to create an EL PV module image that has sufficient diagnostic information to identify faults associated with power loss. The final EL images shown in this work reached representative quality SNRAVG of 4.6, obtained with algorithms developed in previous works. These drone-based EL images were acquired with global horizontal solar irradiance close to one sun in the plane of the array.

In this work we investigate and present preliminary results for two methods for luminescence imaging of photovoltaic (PV) modules in outdoor conditions, with the aim of choosing the most suitable method for implementation on a drone PV plant inspection system. We examined experimentally both electroluminescence (EL) and photoluminescence (PL) PV module imaging methods under natural light conditions, and determined that fast pulsed EL imaging with InGaAs detector cameras can yield reasonably accurate results under daylight conditions. Moreover, we formulated the necessary requirement for a PL light source, which would allow PL imaging of modules under daylight conditions.

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