Impact of duration and missing data on the long-term photovoltaic degradation rate estimation

Accurate quantification of photovoltaic (PV) system degradation rate (RD) is essential for lifetime yield predictions. Although RD is a critical parameter, its estimation lacks a standardized methodology that can be applied on outdoor field data. The purpose of this paper is to investigate the impac...

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Detalhes bibliográficos
Autores: Romero-Fiances, Irene, Livera, Andreas, Theristis, Marios, Makrides, George, Steiner, Joshua S., Nofuentes, Gustavo, De la Casa, Juan, Georghiou, George
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Recursos:Universidad de Jaén
Repositorio:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
OAI Identifier:oai:ruja.ujaen.es:10953/6412
Acesso em linha:https://doi.org/10.1016/j.renene.2021.09.078
https://www.sciencedirect.com/science/article/pii/S096014812101404X
https://hdl.handle.net/10953/6412
Access Level:acceso abierto
Palavra-chave:Missing data
Degradation rate
Performance
Photovoltaic
Time series duration
3322.05
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repository_id_str
spelling Impact of duration and missing data on the long-term photovoltaic degradation rate estimationRomero-Fiances, IreneLivera, AndreasTheristis, MariosMakrides, GeorgeSteiner, Joshua S.Nofuentes, GustavoDe la Casa, JuanGeorghiou, GeorgeMissing dataDegradation ratePerformancePhotovoltaicTime series duration3322.05Accurate quantification of photovoltaic (PV) system degradation rate (RD) is essential for lifetime yield predictions. Although RD is a critical parameter, its estimation lacks a standardized methodology that can be applied on outdoor field data. The purpose of this paper is to investigate the impact of time period duration and missing data on RD by analyzing the performance of different techniques applied to syn-thetic PV system data at different linear RD patterns and known noise conditions. The analysis includes the application of different techniques to a 10-year synthetic dataset of a crystalline Silicon PV system, with emulated degradation levels and imputed missing data. The analysis demonstrated that the ac-curacy of ordinary least squares (OLS), year-on-year (YOY), autoregressive integrated moving average (ARIMA) and robust principal component analysis (RPCA) techniques is affected by the evaluation duration with all techniques converging to lower RD deviations over the 10-year evaluation, apart from RPCA at high degradation levels. Moreover, the estimated RD is strongly affected by the amount of missing data. Filtering out the corrupted data yielded more accurate RD results for all techniques. It is proven that the application of a change-point detection stage is necessary and guidelines for accurate RD estimation are provided.European Commission (ELECTRA project INTEGRATED/ 0918/0071). United States Department of Energy (Solar Energy Technologies Office Award no. 34366) Universidad de Jaén (EDUJA).Elsevier B. V.202520252022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://doi.org/10.1016/j.renene.2021.09.078https://www.sciencedirect.com/science/article/pii/S096014812101404Xhttps://hdl.handle.net/10953/6412reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaéninstname:Universidad de JaénInglésRenewable EnergyAttribution-NonCommercial-NoDerivs 3.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:ruja.ujaen.es:10953/64122026-06-24T12:41:07Z
dc.title.none.fl_str_mv Impact of duration and missing data on the long-term photovoltaic degradation rate estimation
title Impact of duration and missing data on the long-term photovoltaic degradation rate estimation
spellingShingle Impact of duration and missing data on the long-term photovoltaic degradation rate estimation
Romero-Fiances, Irene
Missing data
Degradation rate
Performance
Photovoltaic
Time series duration
3322.05
title_short Impact of duration and missing data on the long-term photovoltaic degradation rate estimation
title_full Impact of duration and missing data on the long-term photovoltaic degradation rate estimation
title_fullStr Impact of duration and missing data on the long-term photovoltaic degradation rate estimation
title_full_unstemmed Impact of duration and missing data on the long-term photovoltaic degradation rate estimation
title_sort Impact of duration and missing data on the long-term photovoltaic degradation rate estimation
dc.creator.none.fl_str_mv Romero-Fiances, Irene
Livera, Andreas
Theristis, Marios
Makrides, George
Steiner, Joshua S.
Nofuentes, Gustavo
De la Casa, Juan
Georghiou, George
author Romero-Fiances, Irene
author_facet Romero-Fiances, Irene
Livera, Andreas
Theristis, Marios
Makrides, George
Steiner, Joshua S.
Nofuentes, Gustavo
De la Casa, Juan
Georghiou, George
author_role author
author2 Livera, Andreas
Theristis, Marios
Makrides, George
Steiner, Joshua S.
Nofuentes, Gustavo
De la Casa, Juan
Georghiou, George
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Missing data
Degradation rate
Performance
Photovoltaic
Time series duration
3322.05
topic Missing data
Degradation rate
Performance
Photovoltaic
Time series duration
3322.05
description Accurate quantification of photovoltaic (PV) system degradation rate (RD) is essential for lifetime yield predictions. Although RD is a critical parameter, its estimation lacks a standardized methodology that can be applied on outdoor field data. The purpose of this paper is to investigate the impact of time period duration and missing data on RD by analyzing the performance of different techniques applied to syn-thetic PV system data at different linear RD patterns and known noise conditions. The analysis includes the application of different techniques to a 10-year synthetic dataset of a crystalline Silicon PV system, with emulated degradation levels and imputed missing data. The analysis demonstrated that the ac-curacy of ordinary least squares (OLS), year-on-year (YOY), autoregressive integrated moving average (ARIMA) and robust principal component analysis (RPCA) techniques is affected by the evaluation duration with all techniques converging to lower RD deviations over the 10-year evaluation, apart from RPCA at high degradation levels. Moreover, the estimated RD is strongly affected by the amount of missing data. Filtering out the corrupted data yielded more accurate RD results for all techniques. It is proven that the application of a change-point detection stage is necessary and guidelines for accurate RD estimation are provided.
publishDate 2022
dc.date.none.fl_str_mv 2022
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.1016/j.renene.2021.09.078
https://www.sciencedirect.com/science/article/pii/S096014812101404X
https://hdl.handle.net/10953/6412
url https://doi.org/10.1016/j.renene.2021.09.078
https://www.sciencedirect.com/science/article/pii/S096014812101404X
https://hdl.handle.net/10953/6412
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Renewable Energy
dc.rights.none.fl_str_mv Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier B. V.
publisher.none.fl_str_mv Elsevier B. V.
dc.source.none.fl_str_mv reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
instname:Universidad de Jaén
instname_str Universidad de Jaén
reponame_str RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
collection RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.81155

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