Investigation of the near-wake behaviour of a utility-scale wind turbine

Aliza Abraham, Teja Dasari, Jiarong Hong

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations


Super-large-scale particle image velocimetry and flow visualization with natural snowfall is used to collect and analyse multiple datasets in the near wake of a 2.5 MW wind turbine. Each dataset captures the full vertical span of the wake from a different perspective. Together, these datasets compose a three-dimensional picture of the near-wake flow, including the effect of the tower and nacelle and the variation of instantaneous wake expansion in response to changes in turbine operation. A region of high-speed flow is observed directly behind the nacelle, and a region of low-speed flow appears behind the tower. Additionally, the nacelle produces a region of enhanced turbulence in its wake while the tower reduces turbulence near the ground as it breaks up turbulent structures in the boundary layer. Analysis of the instantaneous wake behavior reveals variations in wake expansion - and even periods of wake contraction - occurring in response to changes in angle of attack and blade pitch gradient. This behaviour is found to depend on the region of operation of the turbine. These findings can be incorporated into wake models and advanced control algorithms for wind farm optimization and can be used to validate wind turbine wake simulations.

Original languageEnglish (US)
Article number012067
JournalJournal of Physics: Conference Series
Issue number1
StatePublished - Mar 3 2020
EventNorth American Wind Energy Academy, NAWEA 2019 and the International Conference on Future Technologies in Wind Energy 2019, WindTech 2019 - Amherst, United States
Duration: Oct 14 2019Oct 16 2019

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, B. Li, Y. Wu, Y. Liu, J. Tucker, C. Ellis, J. Marr, C. Milliren and D. Christopher for their assistance in the experiments

Publisher Copyright:
© 2020 IOP Publishing Ltd. All rights reserved.


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