Incoming flow measurements of a utility-scale wind turbine using super-large-scale particle image velocimetry

Cheng Li, Aliza Abraham, Biao Li, Jiarong Hong

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

We present incoming flow characterization of a 2.5 ​MW turbine at high spatio-temporal resolution, using super-large-scale particle image velocimetry (SLPIV). The datasets have a field of view of 85 ​m (vertical) × 40 ​m (streamwise) centered at 0.2 rotor diameter upstream. The mean field shows the presence of the induction zone and a distinct region with enhanced vertical velocity. In comparison to vortex theory, SLPIV streamwise velocity presents a steeper velocity drop close to the rotor plane and a more confined induction zone. Time series of nacelle sonic anemometer and SLPIV measured streamwise velocity outside the induction zone show generally matched trends with time-varying discrepancies due to the induction and nacelle effects. The discrepancy, characterized by the sonic-SLPIV velocity ratio, is normally distributed and is less than unity 85% of the time. Data shows both yaw error and incident angle have direct impacts on this ratio, while the intensity of short-term velocity fluctuation has limited effect. Increased yaw error leads to an increase in both the mean and the spread of the ratio. The ratio decreases when the incident angle changes from pointing downward to zero. Further change from zero to pointing upward causes it to plateau with its fluctuations augmented.

Original languageEnglish (US)
Article number104074
JournalJournal of Wind Engineering and Industrial Aerodynamics
Volume197
DOIs
StatePublished - Feb 2020

Bibliographical note

Funding Information:
This work was supported by the National Science Foundation CAREER award (NSF-CBET-1454259), Xcel Energy through the Renewable Development Fund (grant RD4-13) as well as IonE of University of Minnesota. We also thank the students and the engineers from St. Anthony Falls Laboratory, including S. Riley, T. Dasari, Y. Wu, J. Tucker, C. Ellis, J. Marr, C. Milliren and D. Christopher for their assistance in the experiments.

Funding Information:
This work was supported by the National Science Foundation CAREER award ( NSF-CBET-1454259 ), Xcel Energy through the Renewable Development Fund (grant RD4-13 ) as well as IonE of University of Minnesota . We also thank the students and the engineers from St. Anthony Falls Laboratory , including S. Riley, T. Dasari, Y. Wu, J. Tucker, C. Ellis, J. Marr, C. Milliren and D. Christopher for their assistance in the experiments.

Publisher Copyright:
© 2019 Elsevier Ltd

Keywords

  • Incoming flow
  • Induction zone
  • Nacelle anemometer
  • Particle image velocimetry
  • Turbulence
  • Wind turbine

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