Monitoring PWM signals in stand-alone photovoltaic systems

The performance of stand-alone photovoltaic (SAPV) systems can be evaluated by monitoring them in the field using data acquisition systems (DASs). Most SAPV systems use battery charge controllers with pulse width modulation (PWM) to regulate the current into the battery. The PWM signals generated by...

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Autores: Jiménez-Castillo, Gabino, Muñoz-Rodríguez, Francisco José, Rus-Casas , Catalina, Casa-Hernández, Jesús, Tina, Giuseppe Marco
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2019
País:España
Institución:Universidad de Jaén
Repositorio:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
OAI Identifier:oai:ruja.ujaen.es:10953/5822
Acceso en línea:https://doi.org/10.1016/j.measurement.2018.10.075
https://www.sciencedirect.com/science/article/pii/S0263224118310121
https://hdl.handle.net/10953/5822
Access Level:acceso abierto
Palabra clave:Photovoltaic systems
Pulse width modulation
Monitoring
621
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repository_id_str
spelling Monitoring PWM signals in stand-alone photovoltaic systemsJiménez-Castillo, GabinoMuñoz-Rodríguez, Francisco JoséRus-Casas , CatalinaCasa-Hernández, JesúsTina, Giuseppe MarcoPhotovoltaic systemsPulse width modulationMonitoring621The performance of stand-alone photovoltaic (SAPV) systems can be evaluated by monitoring them in the field using data acquisition systems (DASs). Most SAPV systems use battery charge controllers with pulse width modulation (PWM) to regulate the current into the battery. The PWM signals generated by battery charge controllers imply monitoring challenges due to the complexity of this type of signal. In this sense, the aim of this paper is to develop a new and simple monitoring technique for SAPV systems which can estimate the signals provided by a PWM battery charge controller, thus avoiding expensive DASs, simultaneous sampling and the huge amount of collected data. The estimation of PWM signal parameters, such as the duty factor (df) or high and low states, shows high accuracy, with the mean absolute percentage error lower than 1.4%, a mean relative error within 1.4%, and the coefficient of determination higher than 0.9. Furthermore, the proposed technique may easily be used for other electrical devices where PWM is employed.This research was funded by the Agencia Estatal de Investigación,Spain (AEI) and the Fondo Europeo de Desarrollo Regional (FEDER) aimed at the Challenges of Society (Grant No. ENE 2017-83860-R “Nuevos servicios de red para microredes renovables inteligentes. Contribución a la generación distribuida residencial”). The authors wish to thank the University of Jaén for the programme: “Plan de Apoyo a la I+D+I 2014-2015. Prorrogado hasta 2016”.Elsevier202520252019info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttps://doi.org/10.1016/j.measurement.2018.10.075https://www.sciencedirect.com/science/article/pii/S0263224118310121https://hdl.handle.net/10953/5822reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaéninstname:Universidad de JaénInglésMeasurementAttribution-NonCommercial-NoDerivs 3.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:ruja.ujaen.es:10953/58222026-06-24T12:41:07Z
dc.title.none.fl_str_mv Monitoring PWM signals in stand-alone photovoltaic systems
title Monitoring PWM signals in stand-alone photovoltaic systems
spellingShingle Monitoring PWM signals in stand-alone photovoltaic systems
Jiménez-Castillo, Gabino
Photovoltaic systems
Pulse width modulation
Monitoring
621
title_short Monitoring PWM signals in stand-alone photovoltaic systems
title_full Monitoring PWM signals in stand-alone photovoltaic systems
title_fullStr Monitoring PWM signals in stand-alone photovoltaic systems
title_full_unstemmed Monitoring PWM signals in stand-alone photovoltaic systems
title_sort Monitoring PWM signals in stand-alone photovoltaic systems
dc.creator.none.fl_str_mv Jiménez-Castillo, Gabino
Muñoz-Rodríguez, Francisco José
Rus-Casas , Catalina
Casa-Hernández, Jesús
Tina, Giuseppe Marco
author Jiménez-Castillo, Gabino
author_facet Jiménez-Castillo, Gabino
Muñoz-Rodríguez, Francisco José
Rus-Casas , Catalina
Casa-Hernández, Jesús
Tina, Giuseppe Marco
author_role author
author2 Muñoz-Rodríguez, Francisco José
Rus-Casas , Catalina
Casa-Hernández, Jesús
Tina, Giuseppe Marco
author2_role author
author
author
author
dc.subject.none.fl_str_mv Photovoltaic systems
Pulse width modulation
Monitoring
621
topic Photovoltaic systems
Pulse width modulation
Monitoring
621
description The performance of stand-alone photovoltaic (SAPV) systems can be evaluated by monitoring them in the field using data acquisition systems (DASs). Most SAPV systems use battery charge controllers with pulse width modulation (PWM) to regulate the current into the battery. The PWM signals generated by battery charge controllers imply monitoring challenges due to the complexity of this type of signal. In this sense, the aim of this paper is to develop a new and simple monitoring technique for SAPV systems which can estimate the signals provided by a PWM battery charge controller, thus avoiding expensive DASs, simultaneous sampling and the huge amount of collected data. The estimation of PWM signal parameters, such as the duty factor (df) or high and low states, shows high accuracy, with the mean absolute percentage error lower than 1.4%, a mean relative error within 1.4%, and the coefficient of determination higher than 0.9. Furthermore, the proposed technique may easily be used for other electrical devices where PWM is employed.
publishDate 2019
dc.date.none.fl_str_mv 2019
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.1016/j.measurement.2018.10.075
https://www.sciencedirect.com/science/article/pii/S0263224118310121
https://hdl.handle.net/10953/5822
url https://doi.org/10.1016/j.measurement.2018.10.075
https://www.sciencedirect.com/science/article/pii/S0263224118310121
https://hdl.handle.net/10953/5822
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Measurement
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
publisher.none.fl_str_mv Elsevier
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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