@inproceedings{c4d836812c414ab3b26e3dcd10c6d0b0,
  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.",
  author    = "Sergiu Spataru and Harsh Parikh and Benatto, {Gisele Alves dos Reis} and Peter Hacke and Dezso Sera and Poulsen, {Peter Behrensdorff}",
  year      = "2017",
  language  = "English",
  pages     = "1466--1472",
  booktitle = "Proceedings of 33rd European Photovoltaic Solar Energy Conference and Exhibition",
  note      = "33rd European PV Solar Energy Conference and Exhibition, EU PVSEC 2017 ; Conference date: 25-09-2017 Through 29-09-2017",
  url       = "http://www.photovoltaic-conference.com",
}

{"_id":"vZ7LBsGRpyR7iXJqN","bibbaseid":"spataru-parikh-benatto-hacke-sera-poulsen-quantificationofsolarcellfailuresignaturesbasedonstatisticalanalysisofelectroluminescenceimages-2017","author_short":["Spataru, S.","Parikh, H.","Benatto, G.","Hacke, P.","Sera, D.","Poulsen, P."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","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.","author":[{"firstnames":["Sergiu"],"propositions":[],"lastnames":["Spataru"],"suffixes":[]},{"firstnames":["Harsh"],"propositions":[],"lastnames":["Parikh"],"suffixes":[]},{"propositions":[],"lastnames":["Benatto"],"firstnames":["Gisele Alves dos Reis"],"suffixes":[]},{"firstnames":["Peter"],"propositions":[],"lastnames":["Hacke"],"suffixes":[]},{"firstnames":["Dezso"],"propositions":[],"lastnames":["Sera"],"suffixes":[]},{"propositions":[],"lastnames":["Poulsen"],"firstnames":["Peter Behrensdorff"],"suffixes":[]}],"year":"2017","language":"English","pages":"1466–1472","booktitle":"Proceedings of 33rd European Photovoltaic Solar Energy Conference and Exhibition","note":"33rd European PV Solar Energy Conference and Exhibition, EU PVSEC 2017 ; Conference date: 25-09-2017 Through 29-09-2017","url":"http://www.photovoltaic-conference.com","bibtex":"@inproceedings{c4d836812c414ab3b26e3dcd10c6d0b0,\n title = \"Quantification of solar cell failure signatures based on statistical analysis of electroluminescence images\",\n 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.\",\n author = \"Sergiu Spataru and Harsh Parikh and Benatto, {Gisele Alves dos Reis} and Peter Hacke and Dezso Sera and Poulsen, {Peter Behrensdorff}\",\n year = \"2017\",\n language = \"English\",\n pages = \"1466--1472\",\n booktitle = \"Proceedings of 33rd European Photovoltaic Solar Energy Conference and Exhibition\",\n note = \"33rd European PV Solar Energy Conference and Exhibition, EU PVSEC 2017 ; Conference date: 25-09-2017 Through 29-09-2017\",\n url = \"http://www.photovoltaic-conference.com\",\n}","author_short":["Spataru, S.","Parikh, H.","Benatto, G.","Hacke, P.","Sera, D.","Poulsen, P."],"key":"c4d836812c414ab3b26e3dcd10c6d0b0","id":"c4d836812c414ab3b26e3dcd10c6d0b0","bibbaseid":"spataru-parikh-benatto-hacke-sera-poulsen-quantificationofsolarcellfailuresignaturesbasedonstatisticalanalysisofelectroluminescenceimages-2017","role":"author","urls":{"Paper":"http://www.photovoltaic-conference.com"},"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"https://bibbase.org/network/files/kpBnxdqcvffPeZPdM","dataSources":["M8WAZAtDFSB79emzP","E3ujPkAAoZ4m9dxRN"],"keywords":[],"search_terms":["quantification","solar","cell","failure","signatures","based","statistical","analysis","electroluminescence","images","spataru","parikh","benatto","hacke","sera","poulsen"],"title":"Quantification of solar cell failure signatures based on statistical analysis of electroluminescence images","year":2017}