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Offshore Wind, Power Curves and Wakes

Offshore Wind, Power Curves and Wakes. J.Tambke, M.Doerenkaemper, G.Steinfeld, L.v.Bremen & Prof. J.-O.Wolff – ForWind & ICBM University of Oldenburg, Germany Prof. T. Osahwa – University of Kobe, Japan Prof. J.A.T. Bye – The University of Melbourne, Australia. Overview.

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Offshore Wind, Power Curves and Wakes

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  1. Offshore Wind,Power Curves and Wakes J.Tambke, M.Doerenkaemper, G.Steinfeld, L.v.Bremen & Prof. J.-O.Wolff – ForWind & ICBM University of Oldenburg, Germany Prof. T. Osahwa – University of Kobe, Japan Prof. J.A.T. Bye – The University of Melbourne, Australia

  2. Overview • Offshore Performance of Meso-Scale Models • Wind Profiles and Thermal Stratification - FiNO1 • Influence on Power Curves • Influence on Wakes • Large Scale Wakes Slide 2

  3. 100m height / mean wind speed / 2km domain

  4. Capacity Factors Slide 4

  5. FINO1 - 103m height

  6. FiNO1: Influence of Thermal Stratification • Binned Wind-Speed Ratios unstable stable Slide 6

  7. FiNO1: Influence of Thermal Stratification • Binned Wind-Speed Ratios unstable stable Slide 7

  8. Speed Ratio u90./u30 vs. 10m/L Monin-Obukhov Obs. WRF Slide 8

  9. LES: Large Eddy Simulation of Wakes @ alpha ventus 6 month values +1,7% -3% -0,2% u +2,6% -1,5% -0,2% Temporally averaged u at hub height

  10. Influence of Thermal Stability on Power Curves Slide 10

  11. Influence of Thermal Stability on Power Curves Slide 11

  12. Influence of Thermal Stability on Wakes Slide 12

  13. Influence of Thermal Stability on Wakes Slide 13

  14. Conclusions • Thermal Stratificationhas a crucial Impact • on Offshore Wind Profilesand on Wakes • Power differs by up to 10% • Wake effects differ by up to 20% This work was funded by the German BMU within the Project OWEA (RAVE - Research at alpha ventus) Slide 14

  15. MO-Profiles and Boundary Layer Height zi • Mixing Length Approach from Peña & Gryning [BLM 2008]: • Unstable: • Neutral: • Stable: • Boundary Layer Height: Rossby, Montgomery [1935] Slide 15

  16. Speed Ratio (u90./u33) vs. Stability (z/L) stable unstable u(90m) u(33m) <1.05 Stability: 40m./L (Sonic.40m) Slide 16

  17. Speed Ratio (u90./u33) vs. Stability (z/L) Peña/Gryning 2008 Stability: 40m./L (Sonic.40m) Slide 17

  18. Meso-scale Models at FiNO1 FiNO1, alpha ventus Mean Wind Speeds at 100m: ~10m/s Mean Potential Power Production: 50% of the installed Capacity Slide 18

  19. Mean Wind Profiles at FiNO1: DWD, WRF DWD-LME WRF (MYJ-Scheme) Observation for wind directions between 190° and 250° Slide 19

  20. Mean Wind Profiles at FiNO1: 0-200m WRF DWD-LME Observation for wind directions between 190° and 250° Slide 20

  21. Mean WRF-Profiles and Stability unstable -0.6 < 10m/L < +0.6 stable 10m/L -0.6 -0.3 0 +0.3 +0.6 Slide 21

  22. Class 1 Class 2 Class 3 Uncertainty in the Wind Shear due to Temperature Errors Bulk and Gradient Methods to calculate Stability are not accurate enough. U30m= 10 m/s Saint-Drenan et al. EWEC 2009 • Two non calibrated Pt100: (δ(T2-T1) = ± 0.12 – 0.16°C) • Two calibrated Pt100: (δ(T2-T1) = ± 0.08 – 0.12°C) • Temperature difference sensor: (δ(T2-T1) = ± 0.04 – 0.08°C) Slide 22

  23. Comparison of Mean Profiles at FiNO1 Model Input: time series of wind speed at 33m height Observation WAsP bias = - 0.4 m/s MO-ICWP bias < +0.1 m/s RMSE(103m) = 11% RMSE(103m) = 5.5% WAsP MO-ICWP for wind directions between 190° and 250° Slide 23

  24. FiNO1: Comparison of Mean Profiles wind directions between 190° and 250° MM5 (ETA-Scheme o1.5) DWD (prog. TKE o2.5) Observation Slide 24

  25. DWD-LME Speed Ratios vs. Stability (z/L) wind directions between 190° and 250° MM5 (NCEP) DWD Analysis Observation Slide 25

  26. Inertially Coupled Wind Profiles • Motivation for Ekman-Approach: Turbulence Intensities at FiNO1 are very low σu/u vs. Wind Speed (u) at 103m, Jan-Dec 2004 Slide 26

  27. FiNO1: u* -Velocity and Wind Speed at 40m u* (Sonic.40m) Wind Speed (Cup.40m) [m/s] Slide 27

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