Comparing rotor plane induction determined from full-scale measurements and CFD simulations

Research output: Contribution to journalJournal article – Annual report year: 2019Researchpeer-review

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This paper investigates the flow field in the rotor plane of a full-scale operating wind turbine using full-scale light detection and ranging (LiDAR) measurements for the first time. Comparison of the measured flow field with results from large eddy simulations (LES) combined with an actuator line approach is also presented for in-depth study of the induction field in the rotor plane. The measurements include data from two synchronized LiDAR systems—one scanning the undisturbed upstream inflow field and one measuring in the rotor plane. The standard deviation of the mean of velocity time series are and presented as a measure of reliability. The method for calculating the axial velocity based on the line-of-sight velocity is explained and the uncertainty of such method is presented. The process of calculating the yaw misalignment is described. The time-averaged and phase-averaged axial velocity and induction factors are presented relative to radius and azimuth, and the general behavior is described relative to the flow regimes around the blades, tower and nacelle. Simulations and measurements are compared with special emphasis on the flow structures in the vicinity of the individual rotor blades. A convincing agreement between measurements and simulations is demonstrated. The uncertainties originated from the imprecise positions and angles of the measurement instruments are shown. The uncertainties are limited to the middle parts of the blades between 15 m to 25 m from the root. In addition, longer selected time series show smaller uncertainties. This proves the reliability of the application of the methodology for even longer time series.

Original languageEnglish
JournalWind Energy
Volume22
Issue number1
Pages (from-to)109-123
ISSN1095-4244
DOIs
Publication statusPublished - 2019
CitationsWeb of Science® Times Cited: No match on DOI

    Research areas

  • Actuator line, CFD, LiDAR, Rotor plane flow, Spinner LiDAR

ID: 164661761