The Impact of Ice Formation on Wind Turbine Performance and Aerodynamics

1. The Impact of Ice Formation on Wind Turbine Performance and Aerodynamics S. Barber, Y. Wang, S. Jafari, N. Chokani and R.S. Abhari barbers@ethz.ch European Wind Energy Conference, Warsaw 21st April 2010

2. Overview • Motivation • Research objectives • Experimental approach • Results and discussion • Experiment (performance) • CFD (aerodynamics) • Conclusions

3. Icing a Global Challenge for Wind Energy • Wind energy is world’s fastest growing source of electricity production • 160 GW installed wind capacity reached in 2009 • Wind-rich sites must be effectively taken advantage of • Many wind-rich sites are in cold, wet regions Scandinavia & Russia Alps China Northern USA & Canada Decreasing temperature Increasing humidity

4. Icing Dependent on Altitude • Ice formation dependent on many factors, including: • Air humidity • Air density • Air temperature • Wind velocity • Object size on which ice formed • Cloud water droplet concentration • Rate of ice formation therefore highly altitude-dependent: • Altitude 800-1,500m: high risk of ice formation • Altitude > 1,500m: lower risk of ice formation

5. Measured Energy Yield 20% Less Than Predicted • Results from Alpine Test Site Gütsch, Switzerland: 2,300 m altitude • 10-min average power and velocity measurements over a year (Meteotest)* • Corrected for density and hub height • Measured Annual Energy Production 20% less than predicted • Possible reasons: • Icing: investigated here • Gusts and turbulence in complex terrain: being investigated in ETH sub-scale test facility Power curve Annual average of measurements Power (kW) Velocity (m/s) *Barber et al, “Assessment of wind turbine performance in alpine environments,” submitted to J. Wind Eng. Ind. Aero

6. Research Objectives • Quantify performance of wind turbines with specified icing on rotor blades in a systematic, parametric study • Detail impact of icing on aerodynamics

7. 2D profile 2D ice accretion code (LEWICE), atmospheric conditions at Gütsch Span-wise distribution 1000s of photographs from Alpine Test Site Gütsch Specification of Simulated Icing 2D profile + spanwise distribution ≅ simulated icing

8. Specified Ice Shapes low altitude, Bern Jura conditions = “extreme” high-altitude, Gütsch conditions = non-“extreme” 5% chord 5% chord 5% chord 5% chord 5% chord 10% chord

9. ETH Sub-Scale Model Wind Turbine Test Facility • Velocity and acceleration of turbine can be precisely specified: arbitrary velocity profiles • Turbulence intensity can be controlled with grids • Systematic and parametric studies can be carried out: not possible in field • Salient characteristics of facility • For given model & flow velocity, advantage in Reynolds number of factor 15 gained using water as test medium, compared to air • Free-stream turbulence intensity is zero: reliable baseline conditions • Controlled test conditions: accurate assessment of performance due to ice shapes. Summary of test conditions Tip speed ratio = 3 - 8 Re0.75 = 1.4 x 105

10. Model and Instrumentation Rotor geometry: • Blade geometry matches NREL S809 • Interchangeable hub, 2 or 3 bladed Instrumentation: • Torque measured with in-line torquemeter • Torquemeter installed between motor & shaft • Series of tare measurements undertaken to remove drive & seal resistances • Power coefficient: Max. relative errors 3.0% in CP 1.1% in tip speed ratio

11. ETH Sub-Scale Model Matches NREL Turbulent skin friction: Reynolds number correction: corrected uncorrected

12. Effect of Ice on Performance • Ice on outboard 5% of span has most significant effect on performance • Ice removal / prevention systems can be substantially more efficient if their effectiveness is tailored to outboard 5% span of blades No ice

13. Effect of Ice on Performance No ice • Sawtooth shapes do not have significantly different effect on CP compared to smooth shapes • No power generated for Case F (“extreme”) at tip speed ratio ≥ 6

14. “Extreme” Icing Has Large Impact on Annual Energy Production • Annual Energy Production (AEP) • Estimated using IEC standard bins method • Optimal tip speed ratio • Measured wind speeds & atmospheric conditions at Gütsch; icing in 2 months per year Bern Jura conditions / “extreme” • Predicted loss is in good agreement with Gütsch data • Non-”extreme” icing has small impact • “Extreme” icing has large (15% loss) impact Gütsch conditions / non-“extreme” Gütsch measurements

15. CFD Model ANSYS CFX • Commercial, implicit flow solver • One blade, periodic boundaries, k- turbulence model with scalable wall function • Computational grid: 4 million cells R = rotor radius Blade surface 4R Periodic boundary Periodic boundary 4R z y x

16. CFD Results Match Experiments Tip speed ratio = 6 Cp,without ice – CP, with ice (DCP)

17. “Extreme” Ice Causes Extensive Flow Separation Total Velocity (m/s) z-y plane, x = -0.1R Clean Non-“extreme” “Extreme” 3.0 2.0 1.0 0.0 Blade rotation Incidence ≈ 5o Incidence ≈ 5o Incidence ≈ 15o Incidence ≈ 5o Incidence ≈ 5o Incidence ≈ 15o Incidence ≈ 15o Incidence ≈ 15o Incidence ≈ 30o • Flow separation limited to root for non-“extreme” ice • No separation on blade • Flow separation over ¾ of blade for “extreme” ice

18. Conclusions • For icing at high altitudes > 1,500 m: non-”extreme” ice on outboard 5% of the blade has most significant impact on performance → tailor removal systems for outboard 5% of blade • For icing at lower altitudes, 800 – 1,500 m: Annual Energy Production can be reduced up to 15% due to “extreme” ice • At the Alpine Test Site Gütsch, icing does not explain the losses of 20% in Annual Energy Production • Gusts and turbulence are being investigated in the sub-scale model wind turbine test facility at ETH Zurich, which allows testing of dynamically scaled models at near full-scale non-dimensional parameters

19. Acknowledgements • Financial support: Swiss Federal Office of Energy (BFE) • LEC workshop: H. Suter, T. Künzle, C. Troller and C. Reshef barbers@ethz.ch