Quantification of solar cell failure signatures based on statistical analysis of electroluminescence images

Sergiu Spataru, Harsh Parikh, Gisele Alves dos Reis Benatto, Peter Hacke, Dezso Sera, Peter Behrensdorff Poulsen

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

Abstract

We propose a method to identify and quantify the extent of solar cell cracks, shunting, or damaged cell interconnects, present in crystalline silicon photovoltaic (PV) modules by statistical analysis of the electroluminescence (EL) intensity distributions of individual cells within the module. From the EL intensity distributions (ELID) of each cell, we calculated summary statistics such as standard deviation, median, skewness and kurtosis, and analyzed how they correlate with the type of the solar cell degradation.
We found that the dispersion of the ELID increases with the size and severity of the solar cell cracks, correlating with an increase in standard deviation and decrease in kurtosis. For shunted cells, we found that the ELID median is strongly correlated with the extent of cell shunting. Last, cells with damaged interconnect ribbons show current crowding and increased series resistance regions, characterized by increased dispersion and skewness of the ELID. These cell-level diagnostic parameters can be used to quantify the level of mismatch between the solar cells in the module, which can represent the extent of the module degradation, due to transportation, installation, or field operation. The method can be easily automated for quality control by module manufacturers or installers, or can be used as a diagnostic tool by plant operators and diagnostic service providers.
Original languageEnglish
Title of host publicationProceedings of 33rd European Photovoltaic Solar Energy Conference and Exhibition
Publication date2017
Pages1466-1472
Publication statusPublished - 2017
Event33rd European PV Solar Energy Conference and Exhibition - RAI Convention & Exhibition Centre, Amsterdam, Netherlands
Duration: 25 Sep 201729 Sep 2017
Conference number: 33
http://www.photovoltaic-conference.com

Conference

Conference33rd European PV Solar Energy Conference and Exhibition
Number33
LocationRAI Convention & Exhibition Centre
CountryNetherlands
CityAmsterdam
Period25/09/201729/09/2017
Internet address

Cite this

Spataru, S., Parikh, H., Benatto, G. A. D. R., Hacke, P., Sera, D., & Poulsen, P. B. (2017). Quantification of solar cell failure signatures based on statistical analysis of electroluminescence images. In Proceedings of 33rd European Photovoltaic Solar Energy Conference and Exhibition (pp. 1466-1472)
Spataru, Sergiu ; Parikh, Harsh ; Benatto, Gisele Alves dos Reis ; Hacke, Peter ; Sera, Dezso ; Poulsen, Peter Behrensdorff. / Quantification of solar cell failure signatures based on statistical analysis of electroluminescence images. Proceedings of 33rd European Photovoltaic Solar Energy Conference and Exhibition. 2017. pp. 1466-1472
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title = "Quantification of solar cell failure signatures based on statistical analysis of electroluminescence images",
abstract = "We propose a method to identify and quantify the extent of solar cell cracks, shunting, or damaged cell interconnects, present in crystalline silicon photovoltaic (PV) modules by statistical analysis of the electroluminescence (EL) intensity distributions of individual cells within the module. From the EL intensity distributions (ELID) of each cell, we calculated summary statistics such as standard deviation, median, skewness and kurtosis, and analyzed how they correlate with the type of the solar cell degradation. We found that the dispersion of the ELID increases with the size and severity of the solar cell cracks, correlating with an increase in standard deviation and decrease in kurtosis. For shunted cells, we found that the ELID median is strongly correlated with the extent of cell shunting. Last, cells with damaged interconnect ribbons show current crowding and increased series resistance regions, characterized by increased dispersion and skewness of the ELID. These cell-level diagnostic parameters can be used to quantify the level of mismatch between the solar cells in the module, which can represent the extent of the module degradation, due to transportation, installation, or field operation. The method can be easily automated for quality control by module manufacturers or installers, or can be used as a diagnostic tool by plant operators and diagnostic service providers.",
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Spataru, S, Parikh, H, Benatto, GADR, Hacke, P, Sera, D & Poulsen, PB 2017, Quantification of solar cell failure signatures based on statistical analysis of electroluminescence images. in Proceedings of 33rd European Photovoltaic Solar Energy Conference and Exhibition. pp. 1466-1472, 33rd European PV Solar Energy Conference and Exhibition, Amsterdam, Netherlands, 25/09/2017.

Quantification of solar cell failure signatures based on statistical analysis of electroluminescence images. / Spataru, Sergiu; Parikh, Harsh; Benatto, Gisele Alves dos Reis; Hacke, Peter; Sera, Dezso; Poulsen, Peter Behrensdorff.

Proceedings of 33rd European Photovoltaic Solar Energy Conference and Exhibition. 2017. p. 1466-1472.

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

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T1 - Quantification of solar cell failure signatures based on statistical analysis of electroluminescence images

AU - Spataru, Sergiu

AU - Parikh, Harsh

AU - Benatto, Gisele Alves dos Reis

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AU - Sera, Dezso

AU - Poulsen, Peter Behrensdorff

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N2 - We propose a method to identify and quantify the extent of solar cell cracks, shunting, or damaged cell interconnects, present in crystalline silicon photovoltaic (PV) modules by statistical analysis of the electroluminescence (EL) intensity distributions of individual cells within the module. From the EL intensity distributions (ELID) of each cell, we calculated summary statistics such as standard deviation, median, skewness and kurtosis, and analyzed how they correlate with the type of the solar cell degradation. We found that the dispersion of the ELID increases with the size and severity of the solar cell cracks, correlating with an increase in standard deviation and decrease in kurtosis. For shunted cells, we found that the ELID median is strongly correlated with the extent of cell shunting. Last, cells with damaged interconnect ribbons show current crowding and increased series resistance regions, characterized by increased dispersion and skewness of the ELID. These cell-level diagnostic parameters can be used to quantify the level of mismatch between the solar cells in the module, which can represent the extent of the module degradation, due to transportation, installation, or field operation. The method can be easily automated for quality control by module manufacturers or installers, or can be used as a diagnostic tool by plant operators and diagnostic service providers.

AB - We propose a method to identify and quantify the extent of solar cell cracks, shunting, or damaged cell interconnects, present in crystalline silicon photovoltaic (PV) modules by statistical analysis of the electroluminescence (EL) intensity distributions of individual cells within the module. From the EL intensity distributions (ELID) of each cell, we calculated summary statistics such as standard deviation, median, skewness and kurtosis, and analyzed how they correlate with the type of the solar cell degradation. We found that the dispersion of the ELID increases with the size and severity of the solar cell cracks, correlating with an increase in standard deviation and decrease in kurtosis. For shunted cells, we found that the ELID median is strongly correlated with the extent of cell shunting. Last, cells with damaged interconnect ribbons show current crowding and increased series resistance regions, characterized by increased dispersion and skewness of the ELID. These cell-level diagnostic parameters can be used to quantify the level of mismatch between the solar cells in the module, which can represent the extent of the module degradation, due to transportation, installation, or field operation. The method can be easily automated for quality control by module manufacturers or installers, or can be used as a diagnostic tool by plant operators and diagnostic service providers.

M3 - Article in proceedings

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BT - Proceedings of 33rd European Photovoltaic Solar Energy Conference and Exhibition

ER -

Spataru S, Parikh H, Benatto GADR, Hacke P, Sera D, Poulsen PB. Quantification of solar cell failure signatures based on statistical analysis of electroluminescence images. In Proceedings of 33rd European Photovoltaic Solar Energy Conference and Exhibition. 2017. p. 1466-1472