Performance and Equivalent Loads of Wind Turbines in Large Wind Farms.

Transcription

1 Performance and Equivalent Loads of Wind Turbines in Large Wind Farms. Søren Juhl Andersen 1, Jens Nørkær Sørensen, and Robert Mikkelsen May 30, sjan@dtu.dk Andersen Performance of Large Wind Farms. May 30, / 23

2 Overview 3 Simulations 1 Motivation 2 Methodology 4 Results 5 Conclusions Andersen Performance of Large Wind Farms. May 30, / 23

3 Motivation Motivation 3 Simulations 1 Motivation 2 Methodology 4 Results 5 Conclusions Andersen Performance of Large Wind Farms. May 30, / 23

4 Motivation Motivation As the size of wind farms continue to grow, there is an increasing demand for understanding and predicting wake effects. The importance of wake effects are basically related to: Decreased production Increased loads. Photo: Bel Air Aviation, Andersen Performance of Large Wind Farms. May 30, / 23

5 Motivation Motivation The present work presents a database of wind farm simulations, which provides insights into the effect of: Spacing. Freestream wind speed. Turbulence intensity. Photo: Bel Air Aviation, on production and equivalent loads of turbines in large wind farms. Andersen Performance of Large Wind Farms. May 30, / 23

6 Methodology Methodology 3 Simulations 1 Motivation 2 Methodology 4 Results 5 Conclusions Andersen Performance of Large Wind Farms. May 30, / 23

7 Methodology Modelling a Wind Turbine and its Wake Fully coupled LES and aero-elastic codes. Andersen Performance of Large Wind Farms. May 30, / 23

8 Methodology Flow Solver Flow Solver The flow solver EllipSys3D 1 is used to solve the filtered 3D incompressible Navier-Stokes equations: V t + V V = 1 ρ p + [(ν + ν SGS) V ] + 1 ρ f WT + 1 ρ f pbl + 1 ρ f turb. V = 0. where a number of added forces are added to mimic various effects. The velocity(v) is decomposed into a sum of the filtered velocity(v) containing the large scales and the small scales(v ) modelled using a sub-grid scale(sgs) model: V = V + v 1 Michelsen, AFM, 1992 and Sørensen, DTU, 1995 Andersen Performance of Large Wind Farms. May 30, / 23

9 Methodology Turbine Modelling Turbine Modelling: Actuator Line Technique Actuator Line technique 2 introduce lift and drag forces computed using Flex5 into the NS: f 2D = (L, D) = 1 2 ρv 2 relc(c L e L, C D e D ) Based on the relative velocity at the blade section: V rel = V 2 x + (Ωr + V θ) 2 and tabularised lift and drag coefficients, C L (α, Re) and C D (α, Re). x F x L θ V x φ Ωr V θ α γ V rel D F θ 2 Sørensen and Shen, Journal of Fluid Engineering, 2002 Andersen Performance of Large Wind Farms. May 30, / 23

10 Methodology Additional Forcing Prescribed Boundary Layer 25 { U0 (c 2 z 2 + c 1 z) z PBL U pbl (z) = ( U 0 z > PBL ) αpbl z H hub Z Andersen Performance of Large Wind Farms. May 30, / 23 Ū U 0

11 Methodology Turbine NM80 Turbine [ ] Uhub P0 NM80. R = 40m. U rated = 14m/s. P rated = 2.75MW. Variable speed P-controller and PI-pitch angle controller. P[kW ] Uhub Andersen Performance of Large Wind Farms. May 30, / 23

12 Simulations Simulations 3 Simulations 1 Motivation 2 Methodology 4 Results 5 Conclusions Andersen Performance of Large Wind Farms. May 30, / 23

13 Simulations Table: Overview of simulations. *No forces are applied from the turbines to the flow, but aero-elastic results are extracted similar to simulation C. Name U 0 TI Shear Spacing (S X S Y ) Time step Blade resolution Cells in grid O 8m/s 15% R 20R 0.025s A 8m/s 0% R 20R 0.025s B 8m/s 3% R 20R 0.025s C 8m/s 15% R 20R 0.025s D 8m/s 0% R 12R 0.025s E 15m/s 0% R 12R 0.013s F 15m/s 15% R 20R 0.013s G 8m/s 0% R 20R 0.025s H 20m/s 0% R 20R 0.010s I 20m/s 15% R 20R 0.010s Andersen Performance of Large Wind Farms. May 30, / 23

14 Simulations Table: Overview of scaling parameters. Quantity Vhub P MF MY MT T Scaling parameter Maximum mean velocity of all simulations. Rated power Maximum of the mean equivalent flapwise bending moment of all simulations Maximum of the mean equivalent yaw moment of all simulations Maximum of the mean equivalent tilt moment of all simulations Maximum mean thrust force of all simulations Andersen Performance of Large Wind Farms. May 30, / 23

15 Results Results 3 Simulations 1 Motivation 2 Methodology 4 Results 5 Conclusions Andersen Performance of Large Wind Farms. May 30, / 23

16 Results Statistics 1.5 P D E F G H I T D E F G H I M Y D E F G H I Andersen Performance of Large Wind Farms. May 30, / 23

17 Results Statistics V hub A B C P A B C M Y A B C Andersen Performance of Large Wind Farms. May 30, / 23

18 Results Aggregated Statistics 7th-16th turbine, i.e. 510 different 10min periods. (A) + (O) Andersen Performance of Large Wind Farms. May 30, / 23

19 Results Aggregated Statistics (A) (B) (C) (D) (E) (F) (G) (H) (I) Andersen Performance of Large Wind Farms. May 30, / 23

20 Results Aggregated Statistics TI U 0 Spacing Andersen Performance of Large Wind Farms. May 30, / 23

21 Results Farm Layout T M Y P S X S Y [W /m 2 ] P S X S Y [W /m 2 ] Andersen Performance of Large Wind Farms. May 30, / 23

22 Conclusions Conclusions 3 Simulations 1 Motivation 2 Methodology 4 Results 5 Conclusions Andersen Performance of Large Wind Farms. May 30, / 23

23 Conclusions Conclusions Database of full performance and equivalent loads for wind farm simulations incl. effects of turbulence intensity, wind speed, and spacing. Certain scenarios show unexpected peaks for specific turbines. Polar plots are introduced as a means to visually compare the aggregated statistics. Calibration data for lower fidelity models Applied in wind farm design, e.g. include loads to reduce levelized cost of energy, change layout to avoid particular unfavorable conditions at given site, turbines and controllers specifically for waked conditions. Andersen Performance of Large Wind Farms. May 30, / 23

24 Conclusions Acknowledgements Nordic Consortium on Optimization and Control of Wind Farms Eurotech Greentech Wind project CCA on Winds2Loads and LES Thanks for your attention. Andersen Performance of Large Wind Farms. May 30, / 23