Dynamically Variable Blade Geometry for Wind Energy

Cornell UniversityLaboratory for Intelligent Machine Systems

Dynamically Variable Blade Geometry for Wind Energy

Greg Meess, Michael RossDr. Ephrahim Garcia

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AIAA Regional Student Conference

Boston UniversityApril 23-24, 2010

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Goal: Increase wind turbine energy output by morphing blade shape to match changing wind speeds.

Pitch Chord

Twist

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Outline• Motivation• Experimental Design• Airfoil Generation• Simulation• Optimization• Results

– Geometry– Power output

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Motivation• Wind turbines are constantly increasing in size

– Power output is proportional to rotor swept area– The largest turbines cannot be built on land

• Blades are designed for higher wind speeds– Maximize rated power– Turbine spends little time operating at rated power

• Little focus on low wind speeds

– Variable Pitch

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Problem Parameterization • Blade Element Momentum

(BEM) Theory is used• Turbine has operating regime

between 4 m/s and 20 m/s– 4 m/s is lower limit of current

turbines• Fixed speed generator of 60

rpm– Rotations vary from 30 to

120 rpm.• Rayleigh Distribution is used

to assess annual power output

• Chord, twist, and camber are examined

Vestas V90 power output vs. wind speed

Sample wind speed Rayleigh distribution

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Airfoil Generation• NACA XX12 Series

– Leading edge, trailing edge follow NACA equations

– Flexible panels connect to leading edge, rest on trailing edge

– As chord extends/retracts, panels keep airfoil profile

• XFOIL Simulation– CL, CD data collected for angles of

attack between -10° and 45°

NACA 2412 original, fully extended, and fully retracted shapes

Sample data from XFOIL for modified shapes

Emphasize Panels

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Turbine Performance Analysis• Equations based on basic BEM theory,

WT_Perf source code, and Aerodyne Theory Manual.– Blade divided into a number of elements– Axial induction factor initialized

• a = (U1-U2)/U1– Relative wind angle calculated from

normal/tangential velocities– Lift/drag coefficients interpolated from airfoil

data based on angle of attack– Axial induction factor updated– Iterate for conversion– Element torque/power calculated– Total power calculated

Polyamide

Nylon “Kite Wing”

Add stream tube picture

Citations

Crazy airfoil crosssection diagram

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Parametric Study• Performance of morphing blades compared to that of a fixed blade

– Sample blade from WT_Perf optimized across all parameters at wind speed of 10 m/s

– All morphing blades begin with this shape• Each morphing blade changes one parameter

– Three chord scenarios are examined• Extension only• Extension and retraction• Retraction only

Add arrows

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Optimization

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Morphology Plot

Low Speed Shape

High Speed Shape

Variable Pitch

15°

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Morphology Plot

Variable CamberAdd picture

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Highlight new lines

Annual Output Power Curve

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Morphology Surface

Low Speed Shape

High Speed Shape

Variable Chord

Emphasize retraction over others

Define retraction factor

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Highlight new lines

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Morphology Surface

Low Speed Shape

High Speed Shape

Variable Twist

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Highlight new lines

Clarification/vertical lines

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Conclusion

• Variable Twist has the most influence on the performance– Consistent 5% improvement over current pitch control scheme– Achievable using torque tube mechanism– Shape distribution close to linear

wind speed (m/s) retracting chord

variable pitch

variable twist

variable camber

Fair (6.7) 18.64% 23.54% 29.26% 21.77%

Good (7.25) 15.51% 18.45% 23.71% 17.09%

Excellent (7.75) 13.44% 14.98% 20.14% 13.79%

Outstanding (8.4) 11.56% 11.60% 16.99% 10.47%

Superb (10.45) 9.67% 7.51% 14.22% 6.16%

Percent Improvement over Static Blade

Find V-22 paper or illustration

Cite “Fair”, “Good”,etc.

Emphasize improvement over pitch

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Future Work

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Acknowledgements

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Questions & Comments?

Laboratory for Intelligent Machine SystemsAcknowledgements: Professor Sidney Leibovich, Donald Barry