1. Influence of wind characteristics on turbine performance Ioannis Antoniou (1), Rozenn Wagner (1), Søren M. Pedersen (1), Uwe Paulsen (1), Helge A. Madsen (1), Hans E. Jørgensen (1), Kenneth Thomsen (2), Peder Enevoldsen (2), Leo Thesbjerg (3) (1): Wind Energy Department, Risø,DTU (2): Siemens Wind Power (3): Vestas Wind Systems A/S

2. Outline of the presentation Background Wind profile: measurements and classification The analysis method Aeroelastic simulations The wind turbine Input modifications Sensitivity analysis Conclusions

3. Background: Large C p & power curve variations, flat and complex terrain 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 05101520 Wind, mast [m/s] cp / cp_ref [-] Power Curve day/night 0 02468101214161820 WSP Power Large “periodic” performance changes within a short period. The changes in the power curve and Cp are not due to the incorrect performance of the cup anemometers.

4. Are performance changes connected to profile changes and the way performance is measured (hub height) ? Stable atmosphere and high wind shear during night; flat, well- mixed during the day Stable atmosphere with local maximum during the whole day

5. Wind profile measurements and classification at the Høvsøre test site Two met masts used Wind speeds measured at: 10m 40m 60m 80m 100m 116m 165m Sector: 60° to 120° (larger variations relative to the west sector) Wind speed: 6m/s< U<8m/s

6. Wind profile measurements and classification Appr. Profiles normalized at 7m/s 2500 profiles resulted in 173 profile classes (not equally weighted classes)

7. Wind profile measurements and classification Energy Ratio( highest / lowest) >2

8. Wind profile measurements and classification at the Høvsøre test site Examine, with the help of simulations, the influence of: Wind shear Turbulence shear Direction shear......on the power curve

9. Definition of three weighted (“equivalent”) wind speeds

10. Aeroelastic simulations AE_N_Wind/HAWC2 code BEM code implemented in the program User defined mean and turbulence shear input Validated for W/T Siemens 3.6 MW model. Use the normalised profiles as input to identify the sensitivity of the wind field parameters on the w/t performance (mean shear, turbulence shear, wind vector slope and direction changes with height). Time series simulations, to characterise the power performance of the turbine. The Mann turbulence model is used to generate the turbulence field added to the mean field in order to model the random feature of the wind (10 simulations performed per profile).

11. Validation of the code under no-shear and user extreme shear conditions Var rpmCnt. rpm No shear714.888 (kW)703.216 (kW) User shear525.257 (kW)519.744 (kW) ratio:1.3611.353

12. Simulation results using the weighted wind speeds

14. Goodness-of-fit to the turbine’s power curve vs. no of measured profile points

15. Measuring the power curve through a blade mounted Pitot tube

17. A probable explanation The integration of the wind speed over the pitot path, does not weight the wind speeds equally over the rotor profile. Some wind speeds are more represented relative to other ones.

18. Remote sensing using lidars and sodars AQ500

19. Conclusions and future work The profiles from a flat test site have been measured and classified and large variations have been observed in their energy contents Aeroelastic calculations confirm the dependence between the impinging and the resulting energy from the rotor Especially for large turbines, the weighted wind speed over the rotor is better correlated to the turbine power than the simple hub height wind speed. A new definition for power performance measurements is needed. FUTURE WORK Make power curve measurements using remote sensing that covers the whole turbine rotor. Extend the simulations over the whole power curve using the complete w/t model Introduce remote sensing to the standards