Rotational Speed Control Using ANN-Based MPPT for OWC Based on Surface Elevation Measurements
dc.contributor.author | Mzoughi, Fares | |
dc.contributor.author | Garrido Hernández, Izaskun | |
dc.contributor.author | Garrido Hernández, Aitor Josu | |
dc.contributor.author | De la Sen Parte, Manuel | |
dc.date.accessioned | 2021-01-12T11:22:45Z | |
dc.date.available | 2021-01-12T11:22:45Z | |
dc.date.issued | 2020-11-16 | |
dc.identifier | doi: 10.3390/app10248975 | |
dc.identifier.citation | Applied Sciences 10(24) : (2020) // Article ID 8975 | es_ES |
dc.identifier.issn | 2076-3417 | |
dc.identifier.uri | http://hdl.handle.net/10810/49684 | |
dc.description.abstract | This paper presents an ANN-based rotational speed control to avoid the stalling behavior in Oscillating Water Columns composed of a Doubly Fed Induction Generator driven by a Wells turbine. This control strategy uses rotational speed reference provided by an ANN-based Maximum Power Point Tracking. The ANN-based MPPT predicts the optimal rotational speed reference from wave amplitude and period. The neural network has been trained and uses wave surface elevation measurements gathered by an acoustic Doppler current profiler. The implemented ANN-based rotational speed control has been tested with two different wave conditions and results prove the effectiveness of avoiding the stall effect which improved the power generation. | es_ES |
dc.description.sponsorship | This work was supported in part by the Basque Government, through project IT1207-19 and by the MCIU/MINECO through RTI2018-094902-B-C21/RTI2018-094902-B-C22 (MCIU/AEI/FEDER, UE). | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.relation | info:eu-repo/grantAgreement/MCIU/RTI2018-094902-B-C21 | es_ES |
dc.relation | info:eu-repo/grantAgreement/MCIU//RTI2018-094902-B-C22 | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | |
dc.subject | coustic doppler current profiler | es_ES |
dc.subject | artificial neural network | es_ES |
dc.subject | back-to-back converter | es_ES |
dc.subject | oscillating water column | es_ES |
dc.subject | rotational speed control | es_ES |
dc.subject | stalling behavior | es_ES |
dc.subject | wave energy | es_ES |
dc.subject | wells turbine | es_ES |
dc.title | Rotational Speed Control Using ANN-Based MPPT for OWC Based on Surface Elevation Measurements | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.date.updated | 2020-12-24T15:56:34Z | |
dc.rights.holder | 2020 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 (http://creativecommons.org/licenses/by/4.0/). | es_ES |
dc.relation.publisherversion | https://www.mdpi.com/2076-3417/10/24/8975/htm | es_ES |
dc.identifier.doi | 10.3390/app10248975 | |
dc.departamentoes | Ingeniería de sistemas y automática | |
dc.departamentoes | Electricidad y electrónica | |
dc.departamentoeu | Sistemen ingeniaritza eta automatika | |
dc.departamentoeu | Elektrizitatea eta elektronika |
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Except where otherwise noted, this item's license is described as 2020 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 (http://creativecommons.org/licenses/by/4.0/).