Segmented Gurney Flaps for Enhanced Wind Turbine Wake Recovery

Master Thesis (2023)
Author(s)

N.S. Dangi (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

Koen Boorsma – Mentor (TNO - Energy Transition)

E.T.G (Edwin) Bot – Mentor (TNO - Energy Transition)

Wim A.A.M. Bierbooms – Mentor (TU Delft - Wind Energy)

Wei Yu – Mentor (TU Delft - Wind Energy)

S.J. Watson – Graduation committee member (TU Delft - Wind Energy)

Francisco Lopez Dekker – Graduation committee member (TU Delft - Mathematical Geodesy and Positioning)

Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright
© 2023 Nirav Dangi
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Nirav Dangi
Graduation Date
30-05-2023
Awarding Institution
Delft University of Technology
Programme
Electrical Engineering | Sustainable Energy Technology
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
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Abstract

The wind turbine wake is a downstream region of kinetic energy and velocity deficit, higher turbulence and has a complex helical vortex structure. The wind turbine wake’s stability depends mainly on the ambient turbulence and the wind turbine tip- speed ratio. Researchers have developed several wake control techniques to mitigate this issue, such as static axial induction control by torque or pitch control, dynamic axial induction control by pitch control and actuating flaps or other actively controlled add- on devices. Some gaps are present in these methods, in terms of applicability of these techniques in terms of full scale validation and practicality to have the devices as add on to existing blades.

To address these research gaps, this study focuses on designing and evaluating segmented Gurney flaps (in line with the ECN (now TNO Wind Energy) patent by Edwin Bot and Arne Van Garrel) for wind turbine blades to enhance the wake recovery by inducing turbulence in the wake to excite the tip vortices. 4 Gurney flaps were attached in the tip region of each blade of a GE 3.8MW research wind turbine. Field tests were conducted in this study for the wind turbine wake (using a scanning LiDAR to scan a sector up to 5.5D downstream at different altitudes; with a scan time of roughly 3 minutes) and performance analysis (using 10 minute averaged measurement data). Free vortex wake simulations were conducted to validate the faster wake breakdown by the change in lift distribution upon addition of segmented Gurney flaps. Simulations using dynamic blade element momentum theory with IEC NTM inflow conditions from cut in to cut out wind speed were conducted to assess the structural impacts on the retrofitted wind turbine.

The field tests’ wake analysis was quantified with different wind speed, turbulence intensity, wind shear, wind direction conditions. Post processing of LiDAR data involved filtering, creating bin averaged data set, using Gaussian process regression and retrieval of the required wind component. The results show a consistent increase in wake recovery, generally at all downstream distances. The retrofitted configuration results are associated with a higher standard error because of a shorter testing period (due to increased noise levels) than the baseline configuration. The wake simulations indicate an earlier wake break down position, by roughly 2D.

The simulations indicate AEP increase for the retrofitted wind turbine to be roughly +0.2% (+50MWh), at the expense of increased blade and tower structural loads. The wind speed weighted damage equivalent blade flapwise bending moment was found to increase by roughly +2% to +4%; with peaks observed in partial load region of the wind turbine, associated with the operating angle of attack in this region.

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