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dc.contributor.authorFaÿ, François Xavier
dc.contributor.authorRobles Sestafe, Eider ORCID
dc.contributor.authorMarcos Muñoz, Margarita
dc.contributor.authorAldaiturriaga, Endika
dc.contributor.authorFarnández Camacho, Eduardo
dc.date.accessioned2020-06-04T10:31:04Z
dc.date.available2020-06-04T10:31:04Z
dc.date.issued2020-02
dc.identifier.citationRenewable Energy 146 : 1725-1745 (2020)es_ES
dc.identifier.issn0960-1481
dc.identifier.urihttp://hdl.handle.net/10810/43776
dc.description.abstractImproving the power production in wave energy plants is essential to lower the cost of energy production from this type of installations. Oscillating Water Column is among the most studied technologies to convert the wave energy into a useful electrical one. In this paper, three control algorithms are developed to control the biradial turbine installed in the Mutriku Wave Power Plant. The work presents a comparison of their main advantages and drawbacks first from numerical simulation results and then with practical implementation in the real plant, analysing both performance and power integration into the grid. The wave-to-wire model used to develop and assess the controllers is based on linear wave theory and adjusted with operational data measured at the plant. Three different controllers which use the generator torque as manipulated variable are considered. Two of them are adaptive controllers and the other one is a nonlinear Model Predictive Control (MPC) algorithm which uses information about the future waves to compute the control actions. The best adaptive controller and the predictive one are then tested experimentally in the real power plant of Mutriku, and the performance analysis is completed with operational results. A real time sensor installed in front of the plant gives information on the incoming waves used by the predictive algorithm. Operational data are collected during a two-week testing period, enabling a thorough comparison. An overall increase over 30% in the electrical power production is obtained with the predictive control law in comparison with the reference adaptive controller.es_ES
dc.description.sponsorshipThe work was funded by European Union's Horizon 2020 research and innovation program, OPERA Project under grant agreement No 654444, and the Basque Government under project IT1324-19. We acknowledge Ente Vasco de la Energia (EVE) for the access of the Mutriku plant and Oceantec in their support during the sea trials. The authors thank Joannes Berques (Tecnalia) for his contribution on the wave climate analysis at Mutriku and Borja de Miguel (IDOM) for his insights on the hydrodynamics modelling. Special thanks go to Temoana Menard in the study of the polytropic air model during its internship at Tecnalia.es_ES
dc.language.isoenges_ES
dc.publisherPergamon-Elsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/654444es_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectwave energyes_ES
dc.subjectMutrikues_ES
dc.subjectreal sea testinges_ES
dc.subjectpredictive control strategieses_ES
dc.subjectpower take-offes_ES
dc.subjectbiradial turbinees_ES
dc.subjectopera h2020es_ES
dc.subjectperformancees_ES
dc.subjectsystemes_ES
dc.subjectenergy converterses_ES
dc.titleSea trial results of a predictive algorithm at the Mutriku Wave power plant and controllers assessment based on a detailed plant modeles_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0es_ES
dc.rights.holderAtribución 3.0 España*
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0960148119311498?via%3Dihubes_ES
dc.identifier.doi10.1016/j.renene.2019.07.129
dc.contributor.funderEuropean Commission
dc.departamentoesIngeniería de sistemas y automáticaes_ES
dc.departamentoeuSistemen ingeniaritza eta automatikaes_ES


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2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0
Bestelakorik adierazi ezean, itemaren baimena horrela deskribatzen da:2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0