Investigation of Wind Turbine Static Yaw Error Based on Utility-Scale Controlled Experiments

Davide Astolfi, Fabrizio De Caro, Marco Pasetti, Linyue Gao, Ravi Pandit, Alfredo Vaccaro, Jiarong Hong

Research output: Contribution to journalArticlepeer-review

Abstract

Wind 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 under-performance, 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.

Original languageEnglish (US)
Pages (from-to)6559-6568
Number of pages10
JournalIEEE Transactions on Industry Applications
Volume60
Issue number4
DOIs
StatePublished - 2024

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Keywords

  • Wind energy
  • energy systems efficiency
  • renewable energy sources
  • systematic errors
  • wind turbines
  • yaw error

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