Snow-powered research on utility-scale wind turbine flows

Jiarong Hong, Aliza Abraham

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations

Abstract

Abstract: This paper provides a review of the general experimental methodology of snow-powered flow visualization and super-large-scale particle image velocimetry (SLPIV), the corresponding field deployments and major scientific findings from our work on a 2.5 MW utility-scale wind turbine at the Eolos field station. The field measurements were conducted to investigate the incoming flow in the induction zone and the near-wake flows from different perspectives. It has been shown that these snow-powered measurements can provide sufficient spatiotemporal resolution and fields of view to characterize both qualitatively and quantitatively the incoming flow, all the major coherent structures generated by the turbine (e.g., blade, nacelle and tower vortices, etc.) as well as the development and interaction of these structures in the near wake. Our work has further revealed several interesting behaviors of near-wake flows (e.g., wake contraction, dynamic wake modulation, meandering and deflection of the nacelle wake, etc.), and their connections with constantly-changing inflows and turbine operation, which are uniquely associated with utility-scale turbines. These findings have demonstrated that the near wake flows, though highly complex, can be predicted with substantial statistical confidence using supervisory control and data acquisition (SCADA) and structural response information readily available from current utility-scale turbines. Such knowledge can be potentially incorporated into wake development models and turbine controllers for wind farm optimization in the future.

Original languageEnglish (US)
Pages (from-to)339-355
Number of pages17
JournalActa Mechanica Sinica/Lixue Xuebao
Volume36
Issue number2
DOIs
StatePublished - Apr 1 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, B. Li, 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, B. Li, Y. Wu, J. Tucker, C. Ellis, J. Marr, C. Milliren and D. Christopher for their assistance in the experiments.

Publisher Copyright:
© 2020, The Chinese Society of Theoretical and Applied Mechanics and Springer-Verlag GmbH Germany, part of Springer Nature.

Keywords

  • Field measurements
  • PIV
  • Snow visualization
  • Utility-scale
  • Wake
  • Wind turbine

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