Researchers used an InGaAs detector that had a high frame rate to capture sequences of images of solar panel panels. A modulated electric current was then applied. This detector's high imaging speed allowed for more changes to be made between images within the sequence. Credit: YunshengQian, Nanjing University of Science and Technology
Researchers have demonstrated a new method that detects defects in silicon solar panel panels under all weather conditions. The new system will make it easier to maintain solar panels at their optimal performance, as current methods of defect detection cannot be used in daylight conditions.
Around 90 percent of all solar panels are made from silicon. However, defects can occur in manufacturing, installation, or handling. These defects can significantly lower the efficiency of solar panels so it is crucial that they are detected quickly.
Researchers from Nanjing University of Science and Technology, China, describe in the Optica Publishing Group journal Applied Optics how a unique combination of hardware and software makes it possible to clearly image and analyze solar panel defects even in bright sunlight.
YunshengQian, who was the head of the research team, stated that today's defect detection systems cannot be used to detect defects at night on solar panels modules that have been moved into shaded environments or inside. We hope this system will be useful to inspectors at photovoltaic plants in identifying and locating defects faster so they can produce the maximum amount of electricity.
Looking through the light
The researchers developed an all-weather imaging system that can work in any light conditions. They developed software that applied a modulated electrical current to a solar panels, which causes it emit light that switches off and on quickly. This makes defects visible. A high frame rate InGaAs detector is used to capture a series of images of the solar panel as the electric current is applied. Researchers also created a filter to reduce the wavelengths detected to 1150 nm in order to eliminate stray sunlight.
Sheng Wu, the first author of this paper, stated that "the very fast imaging speed allows for more images to be captured so that a greater variety of changes can be distinguished between images." "The breakthrough was an algorithm that differentiates between the unmodulated and modulated parts of an image sequence, and magnifies the difference. This allows for the visible image of the solar panel's defects under high radiation.
The researchers tested the system on both monocrystalline and polycrystalline silicon solar panel panels to see if it works. The system detected defects in silicon-based solar panels at irradiances ranging from 0 to 1300 Watts per squared. This corresponds to light conditions that range from total darkness to full sun.
Researchers have developed a system that detects defects in silicon solar panel panels under full and partial sun. These images were taken under different levels of sunlight. The top row (a), b, and c were taken using a traditional system that does not work in sunlight. The bottom row (d), e, and f were acquired with the new system. Credit: YunshengQian, Nanjing University of Science and Technology
Researchers are currently working on software that reduces digital noise in order to improve image quality and allow the detector to detect image changes with greater accuracy. The researchers also plan to test artificial intelligence on the images acquired to identify defects and streamline the inspection process.
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More information: Sheng Wu et. al., Defect detection method for silicon solar panel under all-day irradiation. Applied Optics (2021). Sheng Wu et al., Defect detection method for silicon solar panel under all-day irradiation. (2021). DOI: 10.1364/AO.435456
