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dc.contributor.authorLekube Garagarza, Jon
dc.contributor.authorGarrido Hernández, Aitor Josu ORCID
dc.contributor.authorGarrido Hernández, Izaskun ORCID
dc.contributor.authorOtaola Santa Coloma, Erlantz
dc.contributor.authorMaseda Rego, Francisco Javier
dc.date.accessioned2018-06-26T10:50:50Z
dc.date.available2018-06-26T10:50:50Z
dc.date.issued2018-02
dc.identifier.citationSensors 18 : (2018) // Article ID 535es_ES
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/10810/27728
dc.description.abstractOceans, and particularly waves, offer a huge potential for energy harnessing all over the world. Nevertheless, the performance of current energy converters does not yet allow us to use the wave energy efficiently. However, new control techniques can improve the efficiency of energy converters. In this sense, the plant sensors play a key role within the control scheme, as necessary tools for parameter measuring and monitoring that are then used as control input variables to the feedback loop. Therefore, the aim of this work is to manage the rotational speed control loop in order to optimize the output power. With the help of outward looking sensors, a Maximum Power Point Tracking (MPPT) technique is employed to maximize the system efficiency. Then, the control decisions are based on the pressure drop measured by pressure sensors located along the turbine. A complete wave-to-wire model is developed so as to validate the performance of the proposed control method. For this purpose, a novel sensor-based flow controller is implemented based on the different measured signals. Thus, the performance of the proposed controller has been analyzed and compared with a case of uncontrolled plant. The simulations demonstrate that the flow control-based MPPT strategy is able to increase the output power, and they confirm both the viability and goodness.es_ES
dc.description.sponsorshipThis work was supported in part by the University of the Basque Country (UPV/EHU) through Project PPG17/33, by the MINECO through the Research Project DPI2015-70075-R (MINECO/FEDER, EU) and by the Basque Government through Elkartek. The authors would like to thank the collaboration of the Basque Energy Agency (EVE) through Agreement UPV/EHUEVE23/6/2011, the Spanish National Fusion Laboratory (EURATOM-CIEMAT) through Agreement UPV/EHUCIEMAT08/190 and EUSKAMPUS - Campus of International Excellence. They would also like to thank Yago Torre-Enciso and Olatz Ajuria from EVE for their collaboration and help. The authors would also like to thank the anonymous reviewers that have helped to improve the initial version of the manuscript.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.relationInfo:eu-repo/grantAgreement/MINECO/DPI2015-70075-Res_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectwave energyes_ES
dc.subjectsensing applicationses_ES
dc.subjectpower managementes_ES
dc.subjectenergy harvestinges_ES
dc.subjectWells turbineses_ES
dc.subjectMutriku power plantes_ES
dc.subjectenergy-conversiones_ES
dc.subjecttriboelectric nanogeneratores_ES
dc.subjectgeneration plantses_ES
dc.subjectwateres_ES
dc.subjectsimulationes_ES
dc.subjectconverteres_ES
dc.subjectnetworkses_ES
dc.subjectsystemes_ES
dc.subjectoutputes_ES
dc.titleFlow Control in Wells Turbines For Harnessing Maximum Wave Poweres_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2018 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.rights.holderAtribución 3.0 España*
dc.relation.publisherversionhttp://www.mdpi.com/1424-8220/18/2/535es_ES
dc.identifier.doi10.3390/s18020535
dc.departamentoesIngeniería de sistemas y automáticaes_ES
dc.departamentoeuSistemen ingeniaritza eta automatikaes_ES


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© 2018 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/).
Except where otherwise noted, this item's license is described as © 2018 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/).