Dec 01, 2014 |
Detecting defects in solar cells
|
(Nanowerk News) Solar panels, or photovoltaic (PV) modules, are being rapidly deployed across the world as costs fall and the need for sustainable, low-carbon energy grows. Being able to effectively characterise PV cells is a key factor in quality control during manufacturing and understanding their long-term behaviour.
|
NPL researchers, Simon Hall, Matt Cashmore and John Blackburn, have developed a new technique for efficiently detecting malfunctioning areas of a PV module.
|
Conventional testing involves scanning the PV cells, row by row, with a laser beam and measuring the current generated in response to the light at a series of points. Spatial variations in the cells' performance can then be identified, but the process is time consuming.
|
In the new method, patterns of light are projected onto the PV cells using a digital micromirror device, such as those found in many office projectors. A technique called compressed sensing is then used to make a map of the current generated by the cells in response to the light, in order to identify malfunctioning areas.
|
|
Patterns of light are projected onto PV cells to measure their response.
|
Compressed sensing is a signal processing technique more commonly used to reconstruct images from relatively few pieces of information, through exploitation of the simplicity of real-world images (when compared to, say, an image made up of random pixels).
|
By assuming that defects are sparse, compressed sensing can identify abnormalities in the PV module using fewer measurements than the traditional raster scanning technique, and without the need for moving parts.
|
Several large companies have already shown interest in adopting the technology for a variety of scanning applications. The team at NPL have recently patented the method, and are now undertaking the necessary developments for it to be put into practice.
|
The work was the subject of the winning poster at last month's NPL Science Poster Fair.
|