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Research Papers: Gas Turbines: Turbomachinery

Implementation, Optimization, and Validation of a Nonlinear Lifting Line-Free Vortex Wake Module Within the Wind Turbine Simulation Code qblade

[+] Author and Article Information
David Marten

Chair of Fluid Dynamics,
Hermann-Föttinger-Institut,
Technische Universität Berlin,
Müller-Breslau-Str. 8,
Berlin D-10623, Germany
e-mail: david.marten@tu-berlin.de

Matthew Lennie, Georgios Pechlivanoglou, Christian Navid Nayeri, Christian Oliver Paschereit

Chair of Fluid Dynamics,
Hermann-Föttinger-Institut,
Technische Universität Berlin,
Müller-Breslau-Str. 8,
Berlin D-10623, Germany

1Corresponding author.

Contributed by the Turbomachinery Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received August 26, 2015; final manuscript received September 30, 2015; published online December 4, 2015. Editor: David Wisler.

J. Eng. Gas Turbines Power 138(7), 072601 (Dec 04, 2015) (10 pages) Paper No: GTP-15-1421; doi: 10.1115/1.4031872 History: Received August 26, 2015; Revised September 30, 2015

The development of the next generation of large multimegawatt wind turbines presents exceptional challenges to the applied aerodynamic design tools. Because their operation is often outside the validated range of current state-of-the-art momentum balance models, there is a demand for more sophisticated, but still computationally efficient simulation methods. In contrast to the blade element momentum method (BEM), the lifting line theory (LLT) models the wake explicitly by a shedding of vortex rings. The wake model of freely convecting vortex rings induces a time-accurate velocity field, as opposed to the annular-averaged induction that is computed from the momentum balance, with computational costs being magnitudes smaller than those of a full computational fluid dynamics (CFD) simulation. The open source code qblade, developed at the Berlin Institute of Technology, was recently extended with a lifting line-free vortex wake algorithm. The main motivation for the implementation of an LLT algorithm into qblade is to replace the unsteady BEM code aerodyn in the coupling to fast to achieve a more accurate representation of the unsteady aerodynamics and to gain more information on the evolving rotor wake and flow-field structure. Therefore, optimization for computational efficiency was a priority during the integration and the provisions that were taken will be presented in short. The implemented LLT algorithm is thoroughly validated against other benchmark BEM, LLT, and panel method codes and experimental data from the MEXICO and National Renewable Energy Laboratory (NREL) Phase VI tests campaigns. By integration of a validated LLT code within qblade and its database, the setup and simulation of LLT simulations are greatly facilitated. Simulations can be run from already existing rotor models without any additional input. Example use cases envisaged for the LLT code include: providing an estimate of the error margin of lower fidelity codes, i.e., unsteady BEM, or providing a baseline solution to check the soundness of higher fidelity CFD simulations or experimental results.

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References

Figures

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Fig. 3

Flowchart of implemented LLT algorithm for one time-step

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Fig. 2

Geometry of a blade panel, position of the lifting line, and shed and trailing vortex line elements

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Fig. 8

Qualitative sketch of rotor in a turbulent wind field with frozen turbulent structures

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Fig. 6

Qualitative sketch of tower influence on velocity field at 15 deg skewed inflow showing areas of flow stagnation and speedup

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Fig. 7

MEXICO rotor Cp with and without tower model, during a step change in velocity from 20 m/s to 15 m/s

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Fig. 4

The qualitative effect of vortex core size on the induced velocity

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Fig. 5

The qualitative effect of turbulent viscosity and time offset on the vortex core size

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Fig. 1

Azimuthal variation of normal force at 82% radius of the MEXICO rotor operating in 30 deg yaw, 3 deg pitch, and 424.5 rpm

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Fig. 9

Example of wake topology and connectivity

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Fig. 10

Illustration of implemented vortex concentration approach

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Fig. 11

Relative error of power output over full rotor revolutions before wake concentration for 3 TSRs

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Fig. 12

Log of the relative error of power output over full rotor revolutions before wake truncation for 3 TSRs

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Fig. 13

Case 1: Ncon = 2.5, Ntrunc = 8, and shed and trailing vortices

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Fig. 14

Case 2: Ncon = 1, Ntrunc = 8, and only trailing vortices

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Fig. 19

MEXICO geometry created in qblade

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Fig. 20

Coordinate system used during MEXICO validation

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Fig. 21

IEA Task 29 Mexnext: normal force variation over blade radius at 15 m/s, yaw = 0 deg

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Fig. 22

IEA Task 29 Mexnext: axial velocity decay at 80% span, yaw = 0 deg, and 0 deg rotor azimuth

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Fig. 23

IEA Task 29 Mexnext: axial velocity traverse parallel to rotor at x_m = 0.15, yaw = 30 deg, and rotor azimuth = 60 deg

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Fig. 24

IEA Task 29 Mexnext: axial velocity traverse parallel to rotor at x_m = 0.15, yaw = 30 deg, and rotor azimuth = 100 deg

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Fig. 25

IEA Task 29 Mexnext: azimuthal variation of normal force at U = 15 m/s, yaw = 30 deg, and pitch = −2.3 deg

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Fig. 26

IEA Task 29 Mexnext: axial velocity traverse at y = −1.4 m, yaw = 30 deg, and 60 deg rotor azimuth

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Fig. 15

NREL Phase VI geometry created in qblade

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Fig. 16

Power curve of the Phase VI rotor, comparison between qblade BEM/LLT and smartrotor panel method

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Fig. 17

Azimuthally averaged power curves for three different cases of yaw (10 deg, 30 deg, and 60 deg) of the MEXICO rotor

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Fig. 18

Free wake structure for three different yaw cases, showing wake nodes only; from left to right: 10 deg yaw, 30 deg yaw, and 60 deg yaw

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