Skip navigation
Please use this identifier to cite or link to this item: http://uvadoc.uva.es/handle/10324/35186
Title: Automatic Quantitative Analysis of Silicon Solar Panels Based on Statistical Parameters from Electro- and Photoluminescence Images [Poster]
Other Titles: European Photovoltaic Solar Energy Conference and Exhibition
Authors: Guada, M.
Pena, S.
Martínez Sacristán, Óscar
González, M.A.
Jiménez López, Juan Ignacio
Pérez, L.
Conference: 35th European Photovoltaic Solar Energy Conference and Exhibition EUPVSEC 2018
EUPVSEC 2018
Issue Date: 2018
Publisher: WIP Renewable Energies
Citation: 35th European Photovoltaic Solar Energy Conference and Exhibition (EUPVSEC 2018), 24 - 28 September 2018, Brussels, Belgium
Abstract: There are many characterization techniques available to evaluate the health of solar panels, such as I-V characterization, infrared thermography (IR), photoluminescence (PL) and electroluminescence (EL). EL imaging has become in recent years a powerful diagnostic tool to evaluate PV modules. EL images allow to detect several defects and degradation modes in the solar cells. The failures are observed as dark contrasted areas in the images. Broad dark regions can be detected even in a low resolution image, while a high resolution image is needed to detect some more specific problems such as cracks, multi-cracks or other line-shaped defects.
Classification: Fotoluminiscencia
Photoluminescence
Sponsor: Junta de Castilla y León (programa de apoyo a proyectos de investigación - Ref. VA081U16)
Ministerio de Economía, Industria y Competitividad (Proyect ENE2014-56069-C4-4-R)
Note: Póster
Publisher Version: www.photovoltaic-conference.com
https://www.eupvsec-planner.com/presentations/c46848/automatic_quantitative_analysis_of_silicon_solar_panels_based_on_statistical_parameters_from_electro-_and_photoluminescence_images.htm
Language: eng
URI: http://uvadoc.uva.es/handle/10324/35186
Rights: info:eu-repo/semantics/openAccess
Appears in Collections:DEP32 - Comunicaciones a congresos, conferencias, etc.

Files in This Item:
File Description SizeFormat 
19_EUPVSEC_2018_Automatic-quantitative-analysis-Silicon-solar.pdf1,6 MBAdobe PDFThumbnail
View/Open

This item is licensed under a Creative Commons License Creative Commons

Suggestions
University of Valladolid
Powered by MIT's. DSpace software, Version 5.5
UVa-STIC