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 | 2024-08-02T11:49:29Z | |
dc.date.available | 2024-08-02T11:49:29Z | |
dc.date.issued | 2024-07 | |
dc.identifier.citation | Energy Conversion and Management X 23 : (2024) // Article ID 100629 | es_ES |
dc.identifier.issn | 2590-1745 | |
dc.identifier.uri | http://hdl.handle.net/10810/69123 | |
dc.description.abstract | Unlike 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.sponsorship | This 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.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation | info:eu-repo/grantAgreement/MICINN/PID2021-123543OBC21 | es_ES |
dc.relation | info:eu-repo/grantAgreement/MICINN/PID2021-123543OB-C22 | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.subject | airflow control | es_ES |
dc.subject | floating offshore wind turbine | es_ES |
dc.subject | adaptive neuro fuzzy inference system | es_ES |
dc.subject | oscillating water column | es_ES |
dc.subject | particle swarm optimization | es_ES |
dc.subject | structural control | es_ES |
dc.title | Metaheuristic Airflow control for vibration mitigation of a hybrid oscillating water Column-Floating offshore wind turbine system | es_ES |
dc.type | info:eu-repo/semantics/article | es_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.holder | Atribución-NoComercial-SinDerivadas 3.0 España | * |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S2590174524001077 | es_ES |
dc.identifier.doi | 10.1016/j.ecmx.2024.100629 | |
dc.departamentoes | Electricidad y electrónica | es_ES |
dc.departamentoes | Ingeniería de sistemas y automática | es_ES |
dc.departamentoeu | Elektrizitatea eta elektronika | es_ES |
dc.departamentoeu | Sistemen ingeniaritza eta automatika | es_ES |