Active Aerodynamic Load Control for Wind Turbine Blades

Active Aerodynamic Load Control for Wind Turbine Blades

Active Aerodynamic Load Control for Wind Turbine Blades

Jose R. Zayas

Sandia National Laboratories

&

C.P. van Dam, R. Chow, J.P. Baker, E.A. Mayda

University of California - Davis

Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company,for the United States Department of Energy under contract DE-AC04-94AL85000.

http://www.ucdavis.edu/

March 01, 2006 EWEC 2006 – Aerodynamics, Aero-Elasticity, Aero-Acoustics, Loads

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OutlineOutline

Problem Statement and Goal Active Control Background Microtab Motivation

CFD work Wind tunnel results

Modeling & Tools Future Work Conclusion



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Problem Statement & GoalProblem Statement & Goal

With Wind Turbines Blades Getting larger and Heavier, Can the Rotor Weight be Reduced by Adding Active Devices?

Can Active Control be Used to Reduce Fatigue Loads?

Can Energy Capture in Low Wind Conditions be Improved?

Research Goal:Understand the Implications and Benefits of Embedded Active Blade Control, Used to Alleviate High Frequency Dynamics



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Active Flow/Load ControlActive Flow/Load Control

• Blade Load Variations Due to Wind Gusts, Direction Changes, and Large Scale Turbulence

• Active Load Control on Blade/Turbine can be Achieved by Modifying:– Blade incidence angle (pitch)

– Flow velocity (modification in RPM)

– Blade length

– Blade aerodynamic characteristics through:• Changes in section shape (aileron, smart materials, microtab)

• Surface blowing/suction

• Other flow control techniques (VG’s, surface heating, plasma)

α

CL

α

CL



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• Active Load Control:– May remove fundamental design constraints– These large benefits are feasible if active control technology is

considered from the onset– May allow for lighter more slender blades designs

• Active Load Control has Already been Implemented in Wind Turbine Design. e.g.:– Yaw control– Blade pitch control– Blade aileron (Zond 750)



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Microtab Concept being ProposedActive Aileron on a Zond 750 Blade

Courtesy: NREL



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Gurney Flap (Passive)Gurney Flap (Passive)

• Gurney Flap (Liebeck, 1978)– Significant increases in CL

– Relatively small increases in CD

– Properly sized Gurney flaps increases in L/D



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Microtab ConceptMicrotab Concept

Evolutionary Development of Gurney flap

Tab Near Trailing Edge Deploys Normal to Surface

Deployment Height on the Order of the Boundary Layer Thickness

Effectively Changes Sectional Camber and Modifies Trailing Edge Flow Development (so-called Kutta condition)



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Microtab ConceptMicrotab Concept

Small, Simple, Fast Response Retractable and Controllable Lightweight, Inexpensive Two-Position “ON-OFF” Actuation Low Power Consumption No Hinge Moments Expansion Possibilities (scalability) Do Not Require Significant Changes to Conventional Lifting

Surface Design (i.e., manufacturing or materials)



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Microtab Research ApproachMicrotab Research Approach

Wind-Tunnel Based Physical Simulations: Pro’s

Proof that concept works as “advertised” Con’s

Requires extensive experimental resources Can be expensive and time consuming Limited to modest chord Reynolds numbers

CFD-Based Numerical Simulations: Pro’s

Relatively fast and inexpensive to study a large number of geometric variations Provides detailed insight to the flow-field phenomena

Con’s Requires extensive computational resources (software & hardware) Learning curve for CFD is steep



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Microtab Research ApproachMicrotab Research Approach

Current Study uses a Closely-Coupled Collaboration Between Computational Fluid Dynamics (CFD) and Wind Tunnel Experimentation

Wind Turbine Dynamic Simulation Pro’s

Gives understanding on the effects to the entire system Cost effective in comparison to field testing Mature codes

Con’s Difficult to capture all of the physics in the model Requires insight and careful validation of the results

Final Goal is to Fly an Effective, Robust Active Load Control System on a Wind Turbine



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CFD MethodsCFD Methods

ARC2D Compressible 2D RANS One-equation Spalart-

Allmaras turbulence model

OVERFLOW 2.0y Compressible 3D RANS Structured Chimera overset

grids Multiple turbulence models

Spalart-Allmaras Menter’s k- SST model



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CFD MethodsCFD Methods

Grid Generation Chimera Grid Tools 1.9 Structured O- and C-type grids 350 to 400 surface grid points y+ < 1.0 for all viscous surfaces



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Wind Tunnel MethodsWind Tunnel Methods

Open Circuit, Low Subsonic Test Section Dimensions

Cross section: 0.86 m 1.22 m (2.8 ft 4.0 ft) Length: 3.66 m (12 ft)

Low Turbulence < 0.1% FS for 80% of test section



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Wind Tunnel MethodsWind Tunnel Methods

Force Measurement Lift and moment

determined using 6-component pyramidal balance

Drag determined using wake measurements Pitot-static probe

measurements Based on Jones’

Method



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Wind Tunnel -vs- CFDWind Tunnel -vs- CFD

Results Repeatedly Show Excellent Agreement Between Computations and Experiment

S809 Baseline Airfoil

1.1% chord tab

95% x/c lower surface

Re = 1×106

Ma = 0.17



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Full System Modeling - Background

Full System Modeling - Background

Wind Turbine Model Micon 65 Stall Regulated 3-bladed upwind Model results have been verified with field data

Dynamic Simulation Tools NuMAD (Numerical Manufacturing and Design Tool)

ANSYS FEA preprocessor Blade property extraction tool (BPE)

FAST (Fatigue, Aerodynamics, Structures, and Turbulence) Modal representation Limited degrees of freedom Used as a preprocessor to ADAMS

ADAMS (Automatic Dynamic Analysis of Mechanical Systems) Commercial multi body dynamic simulation software Virtually unlimited degrees of freedom

Micon 65 – ADAMS Model

NuMAD FEA Model



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FAST –vs- ADAMSFAST –vs- ADAMS

Power vs. Wind Speed

0

20

40

60

80

100

120

3.0 8.0 13.0 18.0

Wind Speed (m/s)

Pow

er (k

W)

FAST

ADAMS

Edgewise moment vs. Wind Speed

-5

-3

-1

1

3

5

7

9

4 9 14 19

Wind Speed (m/s) m

omen

t (kN

m)

FASTADAMS

Codes Provide Virtually Identical Results



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Determining Blade SolidityDetermining Blade Solidity

Outboard Portion of the Blades is Analyzed

Percent Reduction in Flapwise Bending Moments

0%

4%

8%

12%

16%

6 7 8 9 10 11 12

Wind Speed (m/s)

% r

ed

uc

tio

n

9% spanwise tab17% spanwise tab28% spanwise tab37% spanwise tab48% spanwise tab



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Dynamic Effect of Microtabs(no control)

Dynamic Effect of Microtabs(no control)

Rotor Power

22

24

26

28

30

32

34

35.0 36.0 37.0 38.0 39.0 40.0

Time (sec)

Pow

er (K

W)

Baseline

Tabs

Flapwise Moment

12.0

13.0

14.0

15.0

16.0

17.0

18.0

25.0 27.0 29.0 31.0 33.0 35.0

Time (sec)M

omen

t (K

N m

)

Baseline

Tabs

Microtabs Deployed for the Entire Simulation



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Controlled Microtab ResultsControlled Microtab Results

Flapwise Moment

10

12

14

16

18

20

22

6.0 16.0 26.0 36.0 46.0 56.0

Time (sec)

Mo

men

t (K

N m

)

BaselineDelta=10/tabs

Microtabs Response Using Simple Controller



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Future WorkFuture Work

Develop and Analyze Active Control Microtab Airfoil Model for the Wind Tunnel Testing

Quantify Potential Benefits of Microtabs for Increase Energy Capture

Analyze other Potential Devices (flaps, spoilers,…) Model Devices on a Variable Speed / Variable Pitch

Machine (in progress) Develop a MATLAB Simulink Controller for Active Devices



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ConclusionConclusion

Potential Advantages of Active Control have been Investigated

Microtab Analysis has been Quantified both Computationally and Experimentally

Potential Microtab Benefits have been Demonstrated on a Full System Model

Active Devices may Provide Substantial Benefit for Future Wind Turbine Designs



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Thank You!!Thank You!!


Active Aerodynamic Load Control for Wind Turbine Blades

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