Sunlight Variation Study for Drone-Based Daylight Electroluminescence Imaging of PV Modules

Gisele Alves dos Reis Benatto, Claire Mantel, Adrian Alejo Santamaria Lancia, Frederik Villebro, Nicholas Riedel, Sune Thorsteinsson, Peter Poulsen, Søren Forchhammer, Harsh Rajesh Parikh, Sergiu Viorel Spataru, Dezso Séra

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    In this paper, we present a study of daylight EL acquisition and the results of a sunlight variation study in a scenario necessary to assure the increase of EL image quality with denoising by averaging for the robustness of the drone system when bright and intermittently cloudy days occur. It was verified that the indicator of image quality based on the signal-to-noise ratio of EL images has a linear behavior with the amount of averaged images when there is no sun variation. When there are sun irradiance variation, it is observed that the quality decrease even with the increased number of images being averaged, turning to increase again only with further additional images.
    Original languageEnglish
    Title of host publicationProceedings of 36th European Photovoltaic Solar Energy Conference and Exhibition
    Publication date2019
    Pages1651-1655
    ISBN (Print)3-936338-60-4
    DOIs
    Publication statusPublished - 2019
    Event36th European Photovoltaic Solar Energy Conference and Exhibition - Marseille, France
    Duration: 9 Sept 201913 Sept 2019
    Conference number: 36
    https://europa.eu/newsroom/events/36th-european-photovoltaic-solar-energy-conference-and-exhibition-eu-pvsec-2019_en

    Conference

    Conference36th European Photovoltaic Solar Energy Conference and Exhibition
    Number36
    Country/TerritoryFrance
    CityMarseille
    Period09/09/201913/09/2019
    Internet address

    Keywords

    • Electroluminescence imaging
    • PV inspections
    • Fault detection
    • Image processing

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