The Impact of Ice Formation on Wind Turbine Performance
and Aerodynamics
S. Barber, Y. Wang, S. Jafari, N. Chokani and R.S. Abhari
European Wind Energy Conference, Warsaw21st April 2010
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Overview
• Motivation• Research objectives• Experimental approach• Results and discussion
– Experiment (performance)– CFD (aerodynamics)
• Conclusions
• 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
Icing a Global Challenge for Wind Energy
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Northern USA & Canada
Scandinavia & Russia
ChinaAlps
Decreasing temperatureIncreasing humidity
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
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Pow
er (
kW)
Velocity (m/s)
• 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
Measured Energy Yield 20% Less Than Predicted
21.04.10 5*Barber et al, “Assessment of wind turbine performance in alpine environments,” submitted to J. Wind Eng. Ind. Aero
Power curve
Annual average of measurements
Research Objectives
• Quantify performance of wind turbines with specified icing on rotor blades in a systematic, parametric study
• Detail impact of icing on aerodynamics
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Specification of Simulated Icing
2D profile 2D ice accretion code (LEWICE), atmospheric
conditions at Gütsch
Span-wise distribution1000s of photographs from Alpine Test Site
Gütsch
r/R = 0.90 = 8.8o
Vrel = 31.6 m/s
r/R = 0.63 = 8.8o
Vrel = 22.2 m/s
r/R = 0.30 = 6.9o
Vrel = 11.2 m/s
2D profile + spanwise distribution ≅ simulated icing
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Specified Ice Shapes
high-altitude, Gütsch conditions = non-“extreme”
low altitude, Bern Jura conditions = “extreme”
5% chord 5% chord 5% chord 5% chord 5% chord 10% chord
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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
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Model and InstrumentationRotor 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:
CP Trotor
0.5u3Arotor
Max. relative errors3.0% in CP
1.1% in tip speed ratio
Turbulent skin friction:
Reynolds number correction:
ETH Sub-Scale Model Matches NREL
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corrected uncorrected
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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
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Effect of Ice on Performance
• 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
No ice
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“Extreme” Icing Has Large Impact on Annual Energy Production
Gütsch conditions / non-“extreme”
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
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
Gütsch measurements
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CFD ModelANSYS CFX• Commercial, implicit flow solver• One blade, periodic boundaries, k- turbulence model with scalable
wall function• Computational grid: 4 million cells
Blade surface
Periodic boundary Periodic boundary
4R
4R
R = rotor radius
x
y
z
CFD Results Match Experiments
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Tip speed ratio = 6
Cp
,wit
hou
t ic
e –
CP
, w
ith
ice
(C
P)
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“Extreme” Ice Causes Extensive Flow Separation
• Flow separation limited to root for non-“extreme” ice
• No separation on blade
Clean Non-“extreme” “Extreme”
• Flow separation over ¾ of blade for “extreme” ice
3.0
2.0
1.0
0.0
Total Velocity (m/s) z-y plane, x = -0.1R
Blade rotation
Incidence ≈ 15o
Incidence ≈ 5o
Incidence ≈ 5o
Incidence ≈ 15o
Incidence ≈ 5o
Incidence ≈ 5o
Incidence ≈ 30o
Incidence ≈ 15o
Incidence ≈ 15o
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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
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Acknowledgements• Financial support: Swiss Federal Office of Energy (BFE)• LEC workshop: H. Suter, T. Künzle, C. Troller and C.
Reshef
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