Dynamically Variable Blade Geometry for Wind Energy
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Transcript of 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
http://www.terramagnetica.com/2009/08/01/why-are-wind-turbines-getting-bigger/
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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
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Turbine Performance Analysis• Equations based on basic BEM theory1, WT_Perf
source code2, and Aerodyn Theory Manual3.– Blade divided into a number of elements– Power of each element is P= 1/2ρAU34a(1-a)
• Power Coefficient Cp = 4a(1-a)– Axial induction factor defined as a = (U1-U2)/U1– Need initial guess for axial induction factor– Axial induction factor calculated using relative wind
angle, coefficients of lift and drag, tip loss factor– Initial axial induction factor updated– Iterate for convergence– Calculate power
Polyamide
Nylon “Kite Wing”
1 Manwell, J.F., et al., Wind Energy Explained, John Wiley & Sons Ltd., 2002.2 Buhl, Marshall, National Renewable Energy Laboratory, 2004.3 Laino, David and A. Hansen, User’s Guide to Wind Turbine Aerodynamics Software AeroDyn, Windward Engineering, 2002.
Streamtube around wind turbine rotor, used as basis for BEM theory (Manwell 85).
Blade geometry for analysis of horizontal axis wind turbine (Manwell 108).
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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