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dc.contributor.authorRussell, AJ
dc.contributor.authorCollu, M
dc.contributor.authorMcDonald, AS
dc.contributor.authorThies, PR
dc.contributor.authorKeane, A
dc.contributor.authorQuayle, AR
dc.date.accessioned2023-12-15T15:26:27Z
dc.date.issued2024-01-10
dc.date.updated2023-12-15T14:51:22Z
dc.description.abstractNacelle‐mounted, forward‐facing LIDAR technology is able to deliver benefits to rotor speed regulation and loading reductions of floating offshore wind turbines when assisting with blade pitch control in above‐rated wind speed conditions. Large‐scale wind turbines may be subject to significant variations in structural loads due to differences in the wind profile across the rotor‐swept area. These loading fluctuations can be mitigated through the use of individual blade pitch control (IPC). This paper presents a novel LIDAR‐assisted feedforward IPC approach that uses each blade’s rotor azimuth position to allocate an appropriate individual pitch command from a multi‐beam LIDAR. In this computational study, the source code of OpenFAST wind turbine modelling software was modified to enable LIDAR simulation and LIDAR‐assisted control. The LIDAR simulation modifications made are present in the latest OpenFAST release, v3.5. Simulations were performed on a single 15 MW floating offshore wind turbine across the above‐rated wind spectrum and using multiple turbulent wind profiles. Under a turbulent wind field with an average wind speed of 17 ms‐1, the LIDAR‐assisted feedforward IPC delivered root mean squared error and standard deviation reductions to key turbine and substructure parameters by up to 57%. Feedforward IPC delivered enhancements of up to 15% over feedforward collective pitch control, which instead provided the same feedforward command to all blades, compared to the baseline feedback controller. The reductions to the standard deviation and range of the rotor speed may enable structural optimisation of the tower, while the reductions in the variations in the loadings present an opportunity for reduced fatigue damage on turbine components and, consequently, a reduction in maintenance expenditure.en_GB
dc.description.sponsorshipUK Research and Innovationen_GB
dc.identifier.citationVol. 27 (4), pp. 341-362en_GB
dc.identifier.doi10.1002/we.2891
dc.identifier.grantnumberEP/S023933/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/134802
dc.identifierORCID: 0000-0003-3431-8423 (Thies, Philipp)
dc.language.isoenen_GB
dc.publisherWileyen_GB
dc.relation.urlhttps://github.com/ Russell9798/OpenFAST‐v3.4‐Lidar‐IfW‐Original/releases/tag/1.0en_GB
dc.relation.urlhttps://doi.org/10.5281/zenodo.7956023en_GB
dc.relation.urlhttps://github.com/Russell9798/ROSCO‐v2.6‐LAC‐IPC/releases/tag/1.1en_GB
dc.relation.urlhttps://doi.org/10.5281/zenodo.7955992en_GB
dc.relation.urlhttps://zenodo.org/record/8192801en_GB
dc.relation.urlhttps://doi.org/10.5281/zenodo.8192801en_GB
dc.rights© 2024 The Authors. Wind Energy published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
dc.subjectLIDAR‐assisted controlen_GB
dc.subjectFeedforward Controlen_GB
dc.subjectNacelle Mounted LIDARen_GB
dc.subjectIndividual Pitch Controlen_GB
dc.titleLIDAR‐assisted feedforward individual pitch control of a 15 MW floating offshore wind turbineen_GB
dc.typeArticleen_GB
dc.date.available2023-12-15T15:26:27Z
dc.identifier.issn1099-1824
dc.descriptionThis is the final version. Available on open access from Wiley via the DOI in this recorden_GB
dc.descriptionData availability statement: The original modified version of OpenFAST v.3.4, which includes the LIDAR simulator used in this work can be accessed via https://github.com/ Russell9798/OpenFAST‐v3.4‐Lidar‐IfW‐Original/releases/tag/1.0, https://doi.org/10.5281/zenodo.7956023. The modified version of ROSCO v2.6 with the feedforward control additions can be accessed via https://github.com/Russell9798/ROSCO‐v2.6‐LAC‐IPC/releases/tag/1.1, https: //doi.org/10.5281/zenodo.7955992. Simulation datasets used for this paper are available and can be assessed via https://zenodo.org/record/8192801, https://doi.org/10.5281/ zenodo.8192801.en_GB
dc.identifier.eissn1099-1824
dc.identifier.journalWind Energyen_GB
dc.relation.ispartofWind Energy
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2023-12-12
dcterms.dateSubmitted2023-07-31
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2023-12-12
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2023-12-15T14:51:24Z
refterms.versionFCDAM
refterms.dateFOA2024-03-27T13:04:54Z
refterms.panelBen_GB


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© 2024 The Authors. Wind Energy published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's licence is described as © 2024 The Authors. Wind Energy published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.