PERDIGÃO WIND TURBINE WAKE MEASUREMENT

Transcription

1 PERDIGÃO WIND TURBINE WAKE MEASUREMENT Kurt S. Hansen, Robert Menke, Nikola Vasiljevicv & Nikolas Angelou Mail:

2 Outline Objectives Perdigão experiment site description; Measurement setup, modes & sources; Data availability, plots Results Far wake Near wake Quantification of results Conclusion Acknowledgements; 2 DTU Wind Energy, Technical University of Denmark VindKraftNet@EON, Malmö 29. November 2016

3 Objectives (FarmOpt) Development of wind farm optimization tools for optimally placing wind turbines in located in complex terrain. Validation of wind farm models for complex terrain. Requirement: full scale measurements of wind turbine wakes in complex terrain. 3 DTU Wind Energy, Technical University of Denmark VindKraftNet@EON, Malmö 29. November 2016

4 Objectives of the Perdigão experiment To perform an experimental investigation of the flow over a double ridge using two sets of synchronized LiDAR systems (SR & LR windscanners). High quality field data is obtained to investigate: I. Wind resources in complex terrain and hazardous events (NEWA project) II. Inflow conditions for wind turbines in complex terrain (UniTTe & FarmOpt projects) III. Wind turbine wakes in complex terrain (FarmOpt project) 4 DTU Wind Energy, Technical University of Denmark VindKraftNet@EON, Malmö 29. November 2016

5 Perdigão experiment Aim: Collection of high quality field data for model validation (NEWA, UniTTe, FarmOpt) Period: 4. May 29. June 2015 Instrumentation: Hybrid WindScanner System: (3 short- and 3 long-range WindScanners) 20m met mast (cups, vane & sonic) Wind turbine: Enercon E-82 including SCADA data Source: Google Maps 5 DTU Wind Energy, Technical University of Denmark VindKraftNet@EON, Malmö 29. November 2016

6 Site & instrumentation SRWS & LRWS LRWS SRWS WT 6 DTU Wind Energy, Technical University of Denmark VindKraftNet@EON, Malmö 29. November 2016

7 Scanning Modes Hybrid WindScanner System LRWS SRWS RHI Scan Diamond Scan Ridge Scan Virtual Met Mast Scan Wake Scan Inflow Scan 7 DTU Wind Energy, Technical University of Denmark VindKraftNet@EON, Malmö 29. November 2016

8 Instrumentation - SRWS Inflow Wake Scan 8 DTU Wind Energy, Technical University of Denmark VindKraftNet@EON, Malmö 29. November 2016

9 Perdigão site: wind turbine located on a ridge. Ridge SW RHI NE Summit heights m Terrain flats out towards SW and NE Terrain coverage irregular (forest patches of eucalyptus and pine trees) 9 DTU Wind Energy, Technical University of Denmark VindKraftNet@EON, Malmö 29. November 2016

10 Campaign Statistics min periods in total 25h of coinciding measurements 10 DTU Wind Energy, Technical University of Denmark Malmö 29. November 2016

11 Diamond scan for a horizontal, inclined plane, (obtained by 2 x long-range (LR) windscanners) 11 DTU Wind Energy, Technical University of Denmark VindKraftNet@EON, Malmö 29. November 2016

12 LRWS wakes LONG wake SHORT wake 12 DTU Wind Energy, Technical University of Denmark Malmö 29. November 2016

13 Vertical near wake scanning at 1D spacing, (obtained with 3 x short-range (SR) wind scanners) Wake DOWN Wake UP 13 DTU Wind Energy, Technical University of Denmark VindKraftNet@EON, Malmö 29. November 2016

14 Diurnal cycle analysis of identified wake cases. 14 DTU Wind Energy, Technical University of Denmark Malmö 29. November 2016

15 Example of wake deficit distributions 15 DTU Wind Energy, Technical University of Denmark Malmö 29. November 2016

16 Stable Wake Condition 16 DTU Wind Energy, Technical University of Denmark Malmö 29. November 2016

17 Ridge Scan Parallel Flow Maximum deficit=66% Induction: 3-4D Speed recovery: 8-9D 17 DTU Wind Energy, Technical University of Denmark Malmö 29. November 2016

18 Summary of the single wake analysis No overlapping periods for the SR & LR windscanners. Limited number of interesting wake periods due to the narrow inflow sector (10⁰); The wake behaviour correlates with the vertical wind speed. The stability effects seems to determine the wake characteristics (eg. extension, position, dissipation); 18 DTU Wind Energy, Technical University of Denmark Malmö 29. November 2016

19 Conclusion Near wake behaviour can be derived from windscanner measurements through the rotor center; The vertical position of the wake seems to move: Down-hill during nighttime (summer); Up-hill during daytime(summer); The terrain complexity combined with the ambient turbulence, determines the how fast the wind turbine wake dissipates. 19 DTU Wind Energy, Technical University of Denmark Malmö 29. November 2016

20 Acknowledgements Farmopt was funded by the Energy Technology Development and Demonstration Program in 2013 (EUDP), UniTTe was supported by The Danish Council for Strategic Research (DSF) in 2013 and the New European Wind Atlas (NEWA) is supported by the EUROPEAN COMMISSION. 20 DTU Wind Energy, Technical University of Denmark Malmö 29. November 2016