Show simple item record

dc.contributor.authorDerbeli, Mohamed
dc.contributor.authorNapole, Cristian
dc.contributor.authorBarambones Caramazana, Oscar ORCID
dc.contributor.authorSánchez Etchegaray, Jesús María
dc.contributor.authorCalvo Gordillo, Isidro
dc.contributor.authorFernández Bustamante, Pablo
dc.date.accessioned2021-12-09T10:12:50Z
dc.date.available2021-12-09T10:12:50Z
dc.date.issued2021-11-22
dc.identifier.citationEnergies 14(22) : (2021) // Article ID 7806es_ES
dc.identifier.issn1996-1073
dc.identifier.urihttp://hdl.handle.net/10810/54403
dc.description.abstractThis article contains a review of essential control techniques for maximum power point tracking (MPPT) to be applied in photovoltaic (PV) panel systems. These devices are distinguished by their capability to transform solar energy into electricity without emissions. Nevertheless, the efficiency can be enhanced provided that a suitable MPPT algorithm is well designed to obtain the maximum performance. From the analyzed MPPT algorithms, four different types were chosen for an experimental evaluation over a commercial PV system linked to a boost converter. As the reference that corresponds to the maximum power is depended on the irradiation and temperature, an artificial neural network (ANN) was used as a reference generator where a high accuracy was achieved based on real data. This was used as a tool for the implementation of sliding mode controller (SMC), fuzzy logic controller (FLC) and model predictive control (MPC). The outcomes allowed different conclusions where each controller has different advantages and disadvantages depending on the various factors related to hardware and software.es_ES
dc.description.sponsorshipThis research was funded by the Basque Government through the project EKOHEGAZ (ELKARTEK KK-2021/00092), by the Diputación Foral de Álava (DFA), through the project CONAVANTER, and by the UPV/EHU, through the project GIU20/063.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subjectphotovoltaic panelses_ES
dc.subjectmaximum power point tracking (MPPT)es_ES
dc.subjectnonlinear controles_ES
dc.subjectboost converteres_ES
dc.subjectrenewable energieses_ES
dc.titleMaximum Power Point Tracking Techniques for Photovoltaic Panel: A Review and Experimental Applicationses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.date.updated2021-11-25T16:00:37Z
dc.rights.holder2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).es_ES
dc.relation.publisherversionhttps://www.mdpi.com/1996-1073/14/22/7806/htmes_ES
dc.identifier.doi10.3390/en14227806
dc.departamentoesIngeniería de sistemas y automática
dc.departamentoesTecnología electrónica
dc.departamentoesIngeniería eléctrica
dc.departamentoeuSistemen ingeniaritza eta automatika
dc.departamentoeuTeknologia elektronikoa
dc.departamentoeuIngeniaritza elektrikoa


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).