Investigation of temperature coefficients of PV modules through field measured data
•Temperature coefficients of PV modules are determined through long-term field data.•Spectral correction estimates temp coefficients of Isc and Pmax closer to STC values.•M-K test performed shows no monotonic trend of temp coefficients after 8-year exposure.•Temp coefficients for all parameters of t...
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Veröffentlicht in: | Solar energy 2021-08, Vol.224, p.425-439 |
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description | •Temperature coefficients of PV modules are determined through long-term field data.•Spectral correction estimates temp coefficients of Isc and Pmax closer to STC values.•M-K test performed shows no monotonic trend of temp coefficients after 8-year exposure.•Temp coefficients for all parameters of the tested c-Si modules have not degraded.
Varying broadband irradiance and temperature are generally known as the major factors influencing the performance of PV modules, but studies have also shown the substantial impact of spectral variations. In this work, a simple and efficient method to calculate the temperature coefficient using long term data is demonstrated. Temperature coefficients of PV modules are estimated from long term performance data following IEC 60891 standard with additional spectral correction, and are compared against the datasheet values. Significant improvement of correlation coefficient from −0.89 to −0.97 is observed during the regression for maximum power temperature coefficient of two poly-crystalline modules, after spectral correction by spectral factor (SF). Also, the standard deviation of yearly estimated values of these coefficients reduced from 5–7 % to 1–2 %. In another setup involving spectral measurements and various PV technologies, the annual mean of 1.62 eV for average photon energy in 350–1700 nm range, suggests a general blue shift of the spectrum. Higher averages than reference values of useful fraction (UF) for c-Si, CIGS and HIT technologies also validate the blue shift of spectrum. Results show SF produces maximum power temperature coefficients closer to the datasheet values compared to UF, suggesting better applicability of SF as an index for spectral correction. The coefficient values were found closer to STC values and the results from Mann and Kendall test, employed to detect any underlying monotonic trend in the development of temperature coefficients over eight years, showed no increasing or decreasing trend and hence no degradation of temperature coefficients for the long-term exposed PV modules. |
doi_str_mv | 10.1016/j.solener.2021.06.013 |
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Varying broadband irradiance and temperature are generally known as the major factors influencing the performance of PV modules, but studies have also shown the substantial impact of spectral variations. In this work, a simple and efficient method to calculate the temperature coefficient using long term data is demonstrated. Temperature coefficients of PV modules are estimated from long term performance data following IEC 60891 standard with additional spectral correction, and are compared against the datasheet values. Significant improvement of correlation coefficient from −0.89 to −0.97 is observed during the regression for maximum power temperature coefficient of two poly-crystalline modules, after spectral correction by spectral factor (SF). Also, the standard deviation of yearly estimated values of these coefficients reduced from 5–7 % to 1–2 %. In another setup involving spectral measurements and various PV technologies, the annual mean of 1.62 eV for average photon energy in 350–1700 nm range, suggests a general blue shift of the spectrum. Higher averages than reference values of useful fraction (UF) for c-Si, CIGS and HIT technologies also validate the blue shift of spectrum. Results show SF produces maximum power temperature coefficients closer to the datasheet values compared to UF, suggesting better applicability of SF as an index for spectral correction. The coefficient values were found closer to STC values and the results from Mann and Kendall test, employed to detect any underlying monotonic trend in the development of temperature coefficients over eight years, showed no increasing or decreasing trend and hence no degradation of temperature coefficients for the long-term exposed PV modules.</description><identifier>ISSN: 0038-092X</identifier><identifier>EISSN: 1471-1257</identifier><identifier>DOI: 10.1016/j.solener.2021.06.013</identifier><language>eng</language><publisher>New York: Elsevier Ltd</publisher><subject>Broadband ; Correlation coefficient ; Correlation coefficients ; Data sheets ; Degradation ; Irradiance ; Mathematical analysis ; Maximum power ; Modules ; Photovoltaic cells ; Photovoltaics ; Solar energy ; Spectra ; Spectral factor ; Temperature coefficients</subject><ispartof>Solar energy, 2021-08, Vol.224, p.425-439</ispartof><rights>2021 The Author(s)</rights><rights>Copyright Pergamon Press Inc. Aug 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c314t-cbba4507c340a8cfc49d712a3d442f8e90ac15686176ea49555ab0c0b49b4cc53</citedby><cites>FETCH-LOGICAL-c314t-cbba4507c340a8cfc49d712a3d442f8e90ac15686176ea49555ab0c0b49b4cc53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0038092X21004837$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Paudyal, Basant Raj</creatorcontrib><creatorcontrib>Imenes, Anne Gerd</creatorcontrib><title>Investigation of temperature coefficients of PV modules through field measured data</title><title>Solar energy</title><description>•Temperature coefficients of PV modules are determined through long-term field data.•Spectral correction estimates temp coefficients of Isc and Pmax closer to STC values.•M-K test performed shows no monotonic trend of temp coefficients after 8-year exposure.•Temp coefficients for all parameters of the tested c-Si modules have not degraded.
Varying broadband irradiance and temperature are generally known as the major factors influencing the performance of PV modules, but studies have also shown the substantial impact of spectral variations. In this work, a simple and efficient method to calculate the temperature coefficient using long term data is demonstrated. Temperature coefficients of PV modules are estimated from long term performance data following IEC 60891 standard with additional spectral correction, and are compared against the datasheet values. Significant improvement of correlation coefficient from −0.89 to −0.97 is observed during the regression for maximum power temperature coefficient of two poly-crystalline modules, after spectral correction by spectral factor (SF). Also, the standard deviation of yearly estimated values of these coefficients reduced from 5–7 % to 1–2 %. In another setup involving spectral measurements and various PV technologies, the annual mean of 1.62 eV for average photon energy in 350–1700 nm range, suggests a general blue shift of the spectrum. Higher averages than reference values of useful fraction (UF) for c-Si, CIGS and HIT technologies also validate the blue shift of spectrum. Results show SF produces maximum power temperature coefficients closer to the datasheet values compared to UF, suggesting better applicability of SF as an index for spectral correction. The coefficient values were found closer to STC values and the results from Mann and Kendall test, employed to detect any underlying monotonic trend in the development of temperature coefficients over eight years, showed no increasing or decreasing trend and hence no degradation of temperature coefficients for the long-term exposed PV modules.</description><subject>Broadband</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Data sheets</subject><subject>Degradation</subject><subject>Irradiance</subject><subject>Mathematical analysis</subject><subject>Maximum power</subject><subject>Modules</subject><subject>Photovoltaic cells</subject><subject>Photovoltaics</subject><subject>Solar energy</subject><subject>Spectra</subject><subject>Spectral factor</subject><subject>Temperature coefficients</subject><issn>0038-092X</issn><issn>1471-1257</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNqFkMtKxDAUhoMoOI4-glBw3XrSpreVyOBlYEDBC-5Cmp7MpLTNmKQDvr0p497VWfyXw_8Rck0hoUCL2y5xpscRbZJCShMoEqDZCVlQVtKYpnl5ShYAWRVDnX6dkwvnOgBa0qpckLf1eEDn9VZ4bcbIqMjjsEcr_GQxkgaV0lLj6N2svX5Gg2mnHl3kd9ZM212kNPZtNKBwIdBGrfDikpwp0Tu8-rtL8vH48L56jjcvT-vV_SaWGWU-lk0jWA6lzBiISirJ6rakqchaxlJVYQ1C0ryoCloWKFid57loQELD6oZJmWdLcnPs3VvzPYUVvDOTHcNLHkanBZ0zwZUfXdIa5ywqvrd6EPaHU-AzP97xP3585seh4IFfyN0dcxgmHHRQ3QxCYqstSs9bo_9p-AVeNnzN</recordid><startdate>202108</startdate><enddate>202108</enddate><creator>Paudyal, Basant Raj</creator><creator>Imenes, Anne Gerd</creator><general>Elsevier Ltd</general><general>Pergamon Press Inc</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7ST</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope><scope>SOI</scope></search><sort><creationdate>202108</creationdate><title>Investigation of temperature coefficients of PV modules through field measured data</title><author>Paudyal, Basant Raj ; Imenes, Anne Gerd</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c314t-cbba4507c340a8cfc49d712a3d442f8e90ac15686176ea49555ab0c0b49b4cc53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Broadband</topic><topic>Correlation coefficient</topic><topic>Correlation coefficients</topic><topic>Data sheets</topic><topic>Degradation</topic><topic>Irradiance</topic><topic>Mathematical analysis</topic><topic>Maximum power</topic><topic>Modules</topic><topic>Photovoltaic cells</topic><topic>Photovoltaics</topic><topic>Solar energy</topic><topic>Spectra</topic><topic>Spectral factor</topic><topic>Temperature coefficients</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Paudyal, Basant Raj</creatorcontrib><creatorcontrib>Imenes, Anne Gerd</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Environment Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Environment Abstracts</collection><jtitle>Solar energy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Paudyal, Basant Raj</au><au>Imenes, Anne Gerd</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Investigation of temperature coefficients of PV modules through field measured data</atitle><jtitle>Solar energy</jtitle><date>2021-08</date><risdate>2021</risdate><volume>224</volume><spage>425</spage><epage>439</epage><pages>425-439</pages><issn>0038-092X</issn><eissn>1471-1257</eissn><abstract>•Temperature coefficients of PV modules are determined through long-term field data.•Spectral correction estimates temp coefficients of Isc and Pmax closer to STC values.•M-K test performed shows no monotonic trend of temp coefficients after 8-year exposure.•Temp coefficients for all parameters of the tested c-Si modules have not degraded.
Varying broadband irradiance and temperature are generally known as the major factors influencing the performance of PV modules, but studies have also shown the substantial impact of spectral variations. In this work, a simple and efficient method to calculate the temperature coefficient using long term data is demonstrated. Temperature coefficients of PV modules are estimated from long term performance data following IEC 60891 standard with additional spectral correction, and are compared against the datasheet values. Significant improvement of correlation coefficient from −0.89 to −0.97 is observed during the regression for maximum power temperature coefficient of two poly-crystalline modules, after spectral correction by spectral factor (SF). Also, the standard deviation of yearly estimated values of these coefficients reduced from 5–7 % to 1–2 %. In another setup involving spectral measurements and various PV technologies, the annual mean of 1.62 eV for average photon energy in 350–1700 nm range, suggests a general blue shift of the spectrum. Higher averages than reference values of useful fraction (UF) for c-Si, CIGS and HIT technologies also validate the blue shift of spectrum. Results show SF produces maximum power temperature coefficients closer to the datasheet values compared to UF, suggesting better applicability of SF as an index for spectral correction. The coefficient values were found closer to STC values and the results from Mann and Kendall test, employed to detect any underlying monotonic trend in the development of temperature coefficients over eight years, showed no increasing or decreasing trend and hence no degradation of temperature coefficients for the long-term exposed PV modules.</abstract><cop>New York</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.solener.2021.06.013</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Broadband Correlation coefficient Correlation coefficients Data sheets Degradation Irradiance Mathematical analysis Maximum power Modules Photovoltaic cells Photovoltaics Solar energy Spectra Spectral factor Temperature coefficients |
title | Investigation of temperature coefficients of PV modules through field measured data |
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