Koutsourakis, G; Eales, T; Kroeger, I; Blakesley, J C (2021) High-resolution linearity measurements of photovoltaic devices using digital light processing projection. Measurement Science and Technology, 32 (5). 055901 ISSN 0957-0233
Full text not available from this repository.Abstract
Although photovoltaic (PV) devices are rated at Standard Testing Conditions (STC), STC conditions are rarely met, either outdoors, or when PV devices are used for indoor applications. Thus, it is beneficial to fully characterise the linearity of the photovoltaic (PV) devices. Moreover, high accuracy linearity measurements are essential for reference cells, as they ensure the precision of the measured irradiance. This work presents a new technique for linearity measurements of PV devices based on digital light processing (DLP). The proposed system utilises a digital micromirror device coupled with projection optics and a high-power LED array. By creating a series of patterns projected on the device under test with a specific number of bright and dark pixels, linearity measurements can be implemented through a spatial dithering process. Since the dithering process is mechanical, it is expected that any spectral variability effects for the different dithering levels or electrical non-linearities of the light source are avoided. The developed system can provide thousands of measurement points on the linearity curve of a device in seconds, which is impossible with any other currently established methods. Measurements of reference cells with known linearity curves are acquired and are validated by conventional methods. Results demonstrate that the DLP method provides equal measurement accuracy compared to conventional systems, but at significantly higher resolution (points on the linearity curve) and order of magnitude higher measurement speed.
Item Type: | Article |
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Keywords: | Photovoltaics, Solar cells, Non-destructive testing |
Subjects: | Electromagnetics > Electrical Measurement |
Divisions: | Electromagnetic & Electrochemical Technologies |
Identification number/DOI: | 10.1088/1361-6501/abe162 |
Last Modified: | 13 Jul 2021 14:27 |
URI: | http://eprintspublications.npl.co.uk/id/eprint/9221 |
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