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dc.contributor.authorMzoughi, Fares
dc.contributor.authorGarrido Hernández, Izaskun ORCID
dc.contributor.authorGarrido Hernández, Aitor Josu ORCID
dc.contributor.authorDe la Sen Parte, Manuel ORCID
dc.date.accessioned2024-08-02T11:49:29Z
dc.date.available2024-08-02T11:49:29Z
dc.date.issued2024-07
dc.identifier.citationEnergy Conversion and Management X 23 : (2024) // Article ID 100629es_ES
dc.identifier.issn2590-1745
dc.identifier.urihttp://hdl.handle.net/10810/69123
dc.description.abstractUnlike the fixed wind turbines, the structure of Floating Offshore Wind Turbines (FOWT) have the added motions of six degrees of freedom induced by the wind, wave and tidal loads. These motions lead to vibration and the degradation of the structure. This paper presents a novel approach to model and stabilize the FOWT by employing the Oscillating Water Columns (OWC) as active structural control system. The innovative concept involves designing a new floating barge-type platform with integrated OWCs on opposite sides of the platform to mitigate undesired oscillations of the system. These OWCs counteract the bending forces caused by wind on the tower and waves on the barge platform. To synchronize the opposing forces with the system’s tilting, a proposed Particle Swarm Optimization with Decreasing Inertia-based Adaptive Neuro-Fuzzy Inference System (PSODI-ANFIS) airflow control strategy is employed. Through manipulation of the barge platform’s pitch angle, the PSODI-ANFIS airflow control system adjusts the valves on either side, opening one and closing the other accordingly. Simulation results, compared with the standard FOWT as well as the Fuzzy-based airflow control system, demonstrate the effectiveness of the PSODI-ANFIS airflow control. It is shown to be superior in reducing platform pitching and the fore-aft translation of the top tower.es_ES
dc.description.sponsorshipThis work was supported in part through grant IT1555-22 funded by the Basque Government, through grants PID2021-123543OBC21 and PID2021-123543OB-C22 funded by MICIU/AEI/https://doi.org/10.13039/501100011033 and by ERDF/EU and through the María Zambrano grant MAZAM22/15 funded by UPV-EHU/MIU/Next Generation, EU.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/MICINN/PID2021-123543OBC21es_ES
dc.relationinfo:eu-repo/grantAgreement/MICINN/PID2021-123543OB-C22es_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectairflow controles_ES
dc.subjectfloating offshore wind turbinees_ES
dc.subjectadaptive neuro fuzzy inference systemes_ES
dc.subjectoscillating water columnes_ES
dc.subjectparticle swarm optimizationes_ES
dc.subjectstructural controles_ES
dc.titleMetaheuristic Airflow control for vibration mitigation of a hybrid oscillating water Column-Floating offshore wind turbine systemes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.es_ES
dc.rights.holderAtribución-NoComercial-SinDerivadas 3.0 España*
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S2590174524001077es_ES
dc.identifier.doi10.1016/j.ecmx.2024.100629
dc.departamentoesElectricidad y electrónicaes_ES
dc.departamentoesIngeniería de sistemas y automáticaes_ES
dc.departamentoeuElektrizitatea eta elektronikaes_ES
dc.departamentoeuSistemen ingeniaritza eta automatikaes_ES


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© 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.
Except where otherwise noted, this item's license is described as © 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.