Matter & Light

Headlines · 1

1. Oct 19
   Single luminescence image plus lightweight AI maps PV module power loss at about 0.5% error

   A Zhejiang University team led by Dongchen Lan published research in Matter & Light, selected as the journal's October cover: a lightweight AI model first judges from a single luminescence image whether a module's degradation is dominated by defect recombination or by series-resistance losses, and a device physics model then reconstructs local electrical behavior and the power-loss distribution. Validated on about 300 field-recovered crystalline-silicon modules from different production batches and operating environments, the reconstructed maximum power differed from laboratory standard current-voltage measurements by roughly 0.5% overall. The team also tested the method at a 186 kW plant with 342 modules, capturing luminescence images at night from a drone-mounted camera; in one representative area, 24 modules averaged 7.53% power loss, with some severely degraded cell regions near 25%. The team says next steps focus on using the method for routine plant operations and maintenance inspection, and the paper states the approach can extend to perovskite and tandem modules but requires redesign and revalidation.

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