Coherence of turbulent wind at FINO1 Charlotte Obhrai, University of Stavanger, charlotte.obhrai@uis.no University of Stavanger uis.no 4/5/2016 1
Overview Motivation Data selection Results Conclusion 2
Motivation Current wind turbine design standards allows for two different approaches to model the wind field used for engineering estimates The Mann turbulence model and the Kaimal wind spectra combined with a coherence function 3
FINO 1 To avoid mast shadow effects all wind directions in the red sector were excluded 4
Atmospheric stability PGT Stability Class Gradient Richardson Number A Ri < -5.34 very unstable B -5.34 <= Ri <-2.26 unstable C -2.26 <= Ri <-0.569 weakly unstable D -0.569 <= Ri < 0.083 neutral E 0.083 <= Ri <0.196 weakly stable F 0.196 <= Ri < 0.49 stable G 0.49 <= Ri very stable Temperature and wind speed data from the sonics at 80m and 40m were used to calculate the Gradient Richardson number to clasify atmospheric stability 5
Stationarity Removed non-stationary conditions based on the following two criteria Integral length scale Lux > 350m The stationarity of data was also determined by using a runs test (Bendat and Piersol 1986) as follows: 1. Divide the series into time intervals of equal lengths. 2. Compute a mean value (or other, see below) for each interval. 3. Count the number of runs of mean values above and below the median value of the series. 4. Compare the number of counts found to known probabilities of runs for random data. 6
Coherence under neutral wind conditions -0.569 <= Ri < 0.083 Data from January 2008 A total of 4464 records 40% were stationary, neutral and not in the mast shadow Results shown are for wind speed U= 10-11ms -1 7
Average cocoherence 20 m seperation 8
Compare 40m and 20 m seperation 9
Compare to the coherence in IEC 61400-1 Neutral conditions 10
Compare to the coherence in IEC 61400-1 Neutral conditions 11
Coherence under unstable wind conditions -5.34 <= Ri <-2.26 Data from November 2007 A total of 4320 records 58% were stationary, unstable and not in the mast shadow Results shown are for wind speed U= 10-11ms -1 12
Compare to the coherence in IEC 61400-1 Unstable conditions 13
Compare to the coherence in IEC 61400-1 Unstable conditions 14
Coherence under stable wind conditions 0.196 <= Ri < 0.49 Data from may 2008 A total of 4464 records 8% were stationary, stable and not in the mast shadow Results shown are for Wind speed U= 10-11ms -1 15
Compare to the coherence in IEC 61400-1 Stable conditions 16
Compare to the coherence in IEC 61400-1 Stable conditions 17
Msc project to investigate the impact of atmopsheric stability & coherence on the loads and response of a floating offshore wind turbine Please see Rieska s poster for more details 18
Conclusion The Mann turbulence model shows a good agreement with measured values at 40 m separation for the uu and ww cocoherence, but tends to show a lower value at 20 m separation for neutral conditions. The measured vertical uu cocoherence for unstable conditions are significantly higher than values given by both models in the IEC standards. Whereas the opposite is true for stable conditions. Results show the importance to using offshore wind data to determine the appropriate turbulence parameters for wind turbine simulations. Initial results form HAWC2 simulations confirm the sensitivity tower top yaw to varying atmospheric conditions and hence coherence. Planed measurement campaign OBLEX1 will use lidars to measure horizontal coherence as part of the NORCOWE research project. Further work: Investigate the wind coherence using data from at least 1 year to improve accuracy Fit the Manns turbulence model to the measurements for different atmospheric stability conditions Run simulations using HAWC2 using parameter values fitted to the FINO data for different atmospheric conditions and compare those results to parameters given at Høvsøre and in the IEC standards MSc project to be finalized end of June student Rieska Mawarni Putri 19