Detecting wind turbine wakes with nacelle lidars

Transcription

1 Detecting wind turbine wakes with nacelle lidars Dominique Philipp Held 1,2 Jakob Mann 1 Antoine Larvol 2 1 Department of Wind Energy, Technical University of Denmark (DTU) Frederiksborgvej Roskilde, Denmark 2 Windar Photonics A/S Helgeshøj Alle Taastrup, Denmark Correspondence: domhel@dtu.dk

2 Contents 1. Lidar Principle 2. WindEYE Lidar 3. Problem Definition 4. Method & Approach 5. Wake Detection Results 6. Conclusion 2 DTU Wind Energy, Technical University of Denmark

3 Lidar Principle v r Radial wind speed as convolution integral: Power spectrum of detector current W(t, v) 2 important measurement differences compared to cup or sonic anemometers: Volume measurement Low-pass filter effect Measurement of only 1 component of 3D wind vector Freq. or velocity 3 DTU Wind Energy, Technical University of Denmark

4 Windar Photonics 2-beam lidar Derivation of horizontal wind vector components Utilizing 2 line-of-sight wind speeds Assumptions: 1. No vertical wind components 2. Homogeneous inflow 4 DTU Wind Energy, Technical University of Denmark

5 Problem Definition Wake areas violate the homogeneous flow assumption of the misalignment calculation Wind speed reduction in one of the beams is interpreted as yaw misalignment 1-month long experiment on a V52 at Risø Overestimation of yaw misalignment in wake sector 5 DTU Wind Energy, Technical University of Denmark

6 Method & Approach Based on two principles: 1. Lidar averaged turbulence manifests itself in the width of the Doppler peak 1,2 2. Small-scale turbulence is generated inside a turbine wake 3 Wake parameter: 2 nd central moment of Doppler spectrum (Variance) 1 E. Branlard, A. T. Pedersen, J. Mann, N. Angelou, A. Fischer, T. Mikkelsen, M. Harris, C. Slinger and B. F. Montes, "Retrieving wind statistics from average spectrum of continuous-wave," Atmospheric Measurement Techniques, vol. 6, pp , G. C. Larsen, K. S. Hansen, J. Mann, K. Enevoldsen and F. Bingöl, "Full scale measurements of wind turbine wake turbulence," in The Science of Making Torque from Wind, Heraklion, Greece, Larsen, G., Aagaard Madsen, H., Larsen, T. and Troldborg, N.: 2008, Wake modeling and simulation, Technical Report Risø-R-1653(EN), Technical University of Denmark, Risø National Laboratory for Sustainable Energy. 6 DTU Wind Energy, Technical University of Denmark

7 Method & Approach Example of average spectra on the 2 line of sights during a wake situation 7 DTU Wind Energy, Technical University of Denmark

8 Wake Situation 8 DTU Wind Energy, Technical University of Denmark

9 Wake-free Situation 9 DTU Wind Energy, Technical University of Denmark

10 Conclusion & Future Work Doppler peak variance difference indicates wake situations Filter out wake sectors for misalignment Information can also be used for: 1. Turbine derating of upstream turbines (sector management) 2. Wake Deflection Future Work: Comparing different ambient conditions Correlate enhanced wake-turbulence and wake deficit Use wake models to evaluate wake deficit magnitude Apply detection to wind farm control 10 DTU Wind Energy, Technical University of Denmark

11 Thank you for your attention! 11 DTU Wind Energy, Technical University of Denmark

12 Back-up Slides 12 DTU Wind Energy, Technical University of Denmark

13 Wind Speeds and Direction Derivation Line Of Sight Relation under homogeneous flow: Vlos 1,2 = w cos a ± u sin (a) Axial component: w = Vlos1 + Vlos2 2cos(α) Lateral component: u = Vlos2 Vlos1 2sin(α) No influence of the outout-axis position on the measureme nts Incoming Wind Speed: V = u 2 + v 2 Relative Wind Direction ~ Misalignment: φ = tan 1 u w DTU Wind Energy, Technical University of Denmark

14 DTU Wind Energy, Technical University of Denmark Measurement campaign results Estimated AEP gain 2.05%