Modelling Wind Turbine Inflow:
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1 Modelling Wind Turbine Inflow: The Induction zone Alexander R Meyer Forsting Main Supervisor: Niels Troldborg Co-supervisors: Andreas Bechmann & Pierre-Elouan Réthoré
2 Why wind turbine inflow? Inflow KE 1 2 ρρ VV 2 AA VV AA Siemens Gamesa Renewables 2 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
3 Why wind turbine inflow? Power VV 3 VV Blade Forces VV 2 Siemens Gamesa Renewables 3 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
4 How do we get VV? Measure with: Met mast Lidar: Ground-based Hub mounted Siemens Gamesa Renewables 4 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
5 But where do we find VV? Decorrelation: Non-homogeneous wind field Move closer to the turbine Siemens Gamesa Renewables 5 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
6 Showstopper: The induction zone Siemens Gamesa Renewables 6 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
7 Evolution of VV + induction zone Siemens Gamesa Renewables 7 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
8 Benefits of near-rotor measurements Improves wind speed power/load correlation Induction zone Avoids building expensive model met masts Universal measurement procedure UniTTe Nacelle mounted lidars for power and loads assessment 8 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
9 Modelling the induction zone The quest for VV Model validation Physical parameters Simple model CC TT CC TT 9 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
10 Modelling the induction zone The quest for VV Conferences: Torque 2016 Wake Conference 2017 UNCECOMP 2017 Model validation Physical parameters Simple model Meyer Forsting AR et al. Validation of a CFD model with a synchronized triple-lidar system in the wind turbine induction zone. Wind Energy. 2017;20: Meyer Forsting AR, Troldborg N. A finite difference approach to despiking in-stationary velocity data - tested on a triple-lidar. Journal of Physics: Conference Series (Online) Meyer Forsting AR et al.: Modelling lidar volume-averaging and its significance to wind turbine wake measurements: Wake Conference Vol DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
11 Model validation Can we model the induction zone? rr (Medici 2011) xx (Simley 2016) Lines = Models Markers = Wind tunnel measurements 11 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
12 Model validation The triple-lidar measurement campaign Siemens Gamesa Renewables 12 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
13 Model validation (Typical) validation approach yy Model xx 10 x 30 minute periods 1117 Horizontal planes measurement points Siemens Gamesa Renewables 13 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
14 Model validation Low sample size 187 points per horizontal scan 15 seconds for one scan 30 min period = 120 points per grid cell 14 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
15 Model validation Triple-lidar uncertainties Inflow variability Free-stream yy estimate xx 15 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
16 Model validation Triple-lidar uncertainties Free-yawing turbine + fixed measurement grid Coordinate system mismatch 16 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
17 Model validation Triple-lidar uncertainties EllipSys3D Volume- RANS Inflow averaging Steady-state variability Free-stream estimate Spatio-temporal averaging Coordinate Model Actuator disc with airfoil data Log-law ie. neutral stability Measurement system mismatch noise Measurement location 17 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
18 Model validation Stochastic validation approach 3 measurement points taken at different times/horizontal scans close to the rotor Match boundary conditions 18 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
19 Model validation Stochastic validation lidar measurements 8 measurement days All measurements used at once 14 CFD simulations yy xx 19 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
20 Modelling the induction zone The quest for VV Any physical theory is always provisional: you can never prove it Stephen W. Hawking Model validation Physical parameters Simple model 20 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
21 Modelling the induction zone The quest for VV Conferences: Wake Conference 2015 ECCOMAS 2016 Torque 2016 Wind Europe 2016 WES 2017 UNCECOMP 2017 Wake Conference 2017 Model validation Physical parameters Simple model Nathan J, Meyer Forsting AR, Troldborg N, Masson C. Comparison of OpenFOAM and EllipSys3D actuator line methods with (NEW) MEXICO results: Paper. In Wake Conference Meyer Forsting AR, Troldborg N, Gaunaa M. The flow upstream of a row of aligned wind turbine rotors and its effect on power production. Wind Energy. 2017;20(1): Meyer Forsting AR, Bechmann A, Troldborg N. A numerical study on the flow upstream of a wind turbine on complex terrain. Journal of Physics: Conference Series (Online). 2016;753. Mirzaei M, Meyer Forsting AR, Troldborg N. Dynamics of the interaction between the rotor and the induction zone. Journal of Physics: Conference Series (Online). 2016; DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
22 Physical parameters Physics of the induction zone rr max xx/rr 1 uu/vv 0.5 % 1.0 % 2.0 % xx Blade Rotation Wake Rotation Dynamic Load Changes Wind Turbine Yaw & Tilt Thrust Atmospheric turbulence Environment Wind shear > 2.0 % Rotor Design Multiple Turbines Hub Height Topography 22 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
23 Physical parameters Thrust 23 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
24 Physical parameters Thrust Velocity response to a change in thrust coefficient uu CC TT rr xx 24 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
25 Physical parameters Topography 25 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
26 Physical parameters Topography 26 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
27 Physical parameters Topography 27 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
28 Physical parameters Topography αα 11 αα DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
29 Modelling the induction zone The quest for VV Model validation Physical parameters Simple model 29 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
30 Modelling the induction zone The quest for VV Model validation Physical parameters Simple model Troldborg N, Meyer Forsting AR. Wind Energy A simple model of the wind turbine induction zone derived from numerical simulations. Branlard, ESP; Meyer Forsting, AR: Using a cylindrical vortex model to assess the induction zone in front of aligned and yawed rotors. Proceedings of EWEA CC TT CC TT 30 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
31 Simple model Universal induction zone rr/rr xx/rr = 1.5 xx/rr xx/rr = DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
32 Simple model Axial induction behaviour along x rr/rr CC TT = 0.8 xx/rr 32 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
33 Simple model Axial induction behaviour along r Normalised averaged RANS profiles rr/rr xx/rr 33 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
34 Simple model Simple vs CFD r/rr CC TT CC TT xx/rr 34 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
35 Modelling the induction zone The quest for VV Model validation Physical parameters Simple model CC TT CC TT 35 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
36 Conclusions Validated CFD model with a novel stochastic approach Induction zone independant of physical parameters except for the thrust coefficient and topography Possible to describe the axial induction with a simple model 36 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
37 Open Questions Wind farm effects Dynamic load changes Turbulence evolution Complex terrain Possible Impact 0.5% 3.0% 1.0% 5.0% 37 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
38 Outlook Continuing simple model validation Simple radial velocity model Complex terrain: Model validation Include complex physics Model sensitivity 38 DTU Wind Energy, Technical University of Denmark of Denmark
39 Outlook Credit: Antoine Borraccino 39 DTU Wind Energy, Technical University of Denmark of Denmark
40 UniTTe DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
41 Model validation Can we model the induction zone? (Simley 2016) 41 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
42 Model validation Triple-lidar uncertainties Volumeaveraging Spatio-temporal averaging 42 DTU Wind Energy, Technical University of Denmark of Denmark Modelling Wind Turbine Inflow
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