Investigation of wind turbine static yaw error based on utility-scale controlled experiments

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dc.contributor.authorAstolfi, Davide
dc.contributor.authorDe Caro, Fabrizio
dc.contributor.authorPasetti, Marco
dc.contributor.authorGao, Linyue
dc.contributor.authorPandit, Ravi
dc.contributor.authorVaccaro, Alfredo
dc.contributor.authorHong, Jiarong
dc.date.accessioned2024-06-20T14:40:06Z
dc.date.available2024-06-20T14:40:06Z
dc.date.freetoread2024-06-20
dc.date.issued2024-05-08
dc.description.abstractWind energy represents a promising alternative to replace traditional fossil-based energy sources. For this reason, increasing the efficiency in the conversion process from wind to electrical energy is crucial. Unfortunately, the presence of systematic errors (mostly related to the yaw and pitch angles) is one of the key factors causing underperformance, and for this reason, it requires adequate identification. The present work deals with diagnosing wind turbine static yaw error, occurring when the wind vane sensor is incorrectly aligned with the rotor shaft. A thorough investigation methodology is proposed by considering a unique experimental test-up shared by the Eolos Wind Research Station. A utility-scale wind turbine has been imposed to operate subjected to several static yaw errors and reference meteorological data collected nearby the wind turbine were available. By analyzing the relation between the meteorological data and the SCADA data collected by the wind turbine, a systematic alteration in the measurements of nacelle wind speed in the presence of the yaw error is explicitly shown. This phenomenon has been overlooked in the literature and leads to revisiting the methods mostly employed for the diagnosis of the error. Furthermore, a correlation between the presence of static error, increased blade pitch, and heightened levels of tower vibration is observed. In summary, this work provides a comprehensive characterization of the experimental evidence associated with the presence of a wind turbine static yaw error. This paves the way for more effective diagnostic techniques for wind turbine yaw errors, potentially revolutionizing data-driven maintenance strategies.en_UK
dc.identifier.citationAstolfi D, De Caro F, Pasetti M, et al., (2024) Investigation of wind turbine static yaw error based on utility-scale controlled experiments. IEEE Transactions on Industry Applications. Volume 60, Issue 4, July-August 2024, pp. 6559-6568en_UK
dc.identifier.eissn1939-9367
dc.identifier.issn0093-9994
dc.identifier.urihttps://doi.org/10.1109/TIA.2024.3397956
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/22542
dc.identifier.volumeNo60
dc.language.isoen_UKen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectWind Energyen_UK
dc.subjectWind Turbinesen_UK
dc.subjectSystematic Errorsen_UK
dc.subjectYaw Erroren_UK
dc.subjectRenewable Energy Sourcesen_UK
dc.subjectEnergy Systems Efficiencyen_UK
dc.titleInvestigation of wind turbine static yaw error based on utility-scale controlled experimentsen_UK
dc.typeArticleen_UK
dcterms.dateAccepted2024-04-25

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