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dc.contributor.authorRussell, A
dc.contributor.authorCollu, M
dc.contributor.authorMcDonald, A
dc.contributor.authorThies, P
dc.contributor.authorMortimer, A
dc.contributor.authorQuayle, A
dc.date.accessioned2023-11-24T14:27:08Z
dc.date.issued2023-09-22
dc.date.updated2023-11-24T13:09:29Z
dc.description.abstractNacelle-mounted, forward-facing Light Detection and Ranging (LIDAR) technology is able to measure the wind field as it approaches a wind turbine. Knowledge of the incoming wind can be used for feedforward turbine control, enabling torque, pitch or yaw systems in advance of the wind’s impact. This can enhance turbine performance through improved rotor speed regulation and power capture, while reducing structural loads. LIDAR has previously exhibited its most significant benefits for turbine performance when assisting with blade pitch control in above-rated wind speed conditions. The impact of feedforward pitch control implementation in floating offshore wind turbines is expected to vary for different substructures due to their differing natural frequencies of motion and rates of feedback pitch control actuation, as a consequence of modified controller gains required to overcome negative damping. This computational study outlines the LIDAR-assisted feedforward pitch control implementation approach, and compares its impacts on two floating substructures supporting the IEA 15 MW reference turbine: the UMaine VolturnUS-S Semi-Submersible and the WindCrete Spar. Under turbulent wind conditions and by using a LIDAR simulator to capture the incoming wind field, both floating turbine configurations benefitted from LIDAR-assisted feedforward pitch control, through improved rotor speed regulation by up to 33%, reduced loads by up to 17% and platform motions by up to 19%. These performance improvements can lead to reduced component failure rates, maintenance, and, ultimately, reduced lifetime operations and maintenance expenditure.en_GB
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC)en_GB
dc.identifier.citationASME 2023: 42nd International Conference on Ocean, Offshore and Arctic Engineering, 11 - 16 June 2023, Melbourne, Australia. Paper No. OMAE2023-100822en_GB
dc.identifier.doihttps://doi.org/10.1115/omae2023-100822
dc.identifier.grantnumberEP/S023933/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/134637
dc.identifierORCID: 0000-0003-3431-8423 (Thies, Philipp)
dc.identifierScopusID: 55134959500 (Thies, Philipp)
dc.identifierResearcherID: H-2490-2011 (Thies, Philipp)
dc.language.isoenen_GB
dc.publisherAmerican Society of Mechanical Engineers (ASME)en_GB
dc.rights© 2023 ASME. This version is made available under the CC-BY 4.0 license: https://creativecommons.org/licenses/by/4.0/en_GB
dc.subjectLIDARen_GB
dc.subjectLIDAR-assisted Controlen_GB
dc.subjectFeedforward Controlen_GB
dc.subjectFloating Offshore Winden_GB
dc.titleLIDAR-Assisted Feedforward Pitch Control of 15 MW Floating Offshore Wind Turbinesen_GB
dc.typeConference paperen_GB
dc.date.available2023-11-24T14:27:08Z
dc.identifier.isbn9780791886908
dc.descriptionThis is the author accepted manuscript. The final version is available from ASME via the DOI in this recorden_GB
dc.relation.ispartofProceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE, 8
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2023-09-22
rioxxterms.typeConference Paper/Proceeding/Abstracten_GB
refterms.dateFCD2023-11-24T14:24:49Z
refterms.versionFCDAM
refterms.dateFOA2023-11-24T14:27:12Z
refterms.panelBen_GB
refterms.dateFirstOnline2023-09-22
pubs.name-of-conferenceVolume 8: Ocean Renewable Energy


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© 2023 ASME. This version is made available under the CC-BY 4.0 license: https://creativecommons.org/licenses/by/4.0/
Except where otherwise noted, this item's licence is described as © 2023 ASME. This version is made available under the CC-BY 4.0 license: https://creativecommons.org/licenses/by/4.0/