1. Dynamically Variable Blade Geometry for Wind Energy
Greg Meess, Michael Ross
Dr. Ephrahim Garcia
Laboratory for Intelligent Machine Systems
AIAA Regional Student Conference
Boston University
April 23-24, 2010

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

3. Outline Motivation Experimental Design Airfoil Generation Simulation
Optimization
Results
Geometry
Power output

4. 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

5. 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

6. Airfoil Generation NACA XX12 Series XFOIL Simulation
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

7. 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
Streamtube around wind turbine rotor, used as basis for BEM theory (Manwell 85).
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.
Blade geometry for analysis of horizontal axis wind turbine (Manwell 108).

8. 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
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10. Optimization

11. Variable Pitch
Low Speed Shape
Morphology Plot
15°
High Speed Shape

13. Variable Camber
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Morphology Plot

14. Annual Output
Power Curve
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15. Variable Chord Low Speed Shape Define retraction factor
High Speed Shape
Emphasize retraction over others
Morphology Surface

16. Highlight new lines

17. Variable Twist
Low Speed Shape
Morphology Surface
High Speed Shape

18. Highlight new lines
Clarification/vertical lines

19. Conclusion Cite “Fair”, “Good”,etc.
Percent Improvement over Static Blade
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%
Emphasize improvement over pitch
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
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20. Future Work

21. Acknowledgements
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22. Questions & Comments?
Laboratory for Intelligent Machine Systems Acknowledgements: Professor Sidney Leibovich, Donald Barry