Validation of a Prediction Model for Control of Micro Wind Turbines

1. Validation of a Prediction Model for Control of Micro Wind Turbines Ryan McGowan and Narayanan Komerath Daniel Guggenheim School of Aerospace Engineering Georgia Institute of Technology Atlanta, Georgia USA INTERNATIONAL CONFERENCE ON POWER, SIGNALS, CONTROL AND COMPUTATIONS Trissur, India, January 3-06, 2012

2. SUMMARY Aim Objective Optimize design for low tip-speed ratio • Develop micro wind turbine for • single-family use in India • Vertical axis vs. horizontal axis • Local manufacture & maintenance • Lifecycle safety & environment • Technically complex to design! TSR = Blade tip tangential\ Windspeed • Operation at low wind speeds • Low blade tip speed TSR Methods • Aerodynamics simulation validated • Low Reynolds number corrections • Wind tunnel testbed • Azimuthal modification strategy to improve operation • Real-time control options

3. Vertical Axis Wind Turbine • Bicycle-based 1m VAWT >270rpm, • >70 w (mechanical) • 2. 2m 1kW VAWT for high coastal winds. • Issues: • Optimal tip speed ratio 2 to 5 – too high. • Variable power transmission • Nonlinear pitch control • Flexible blade operation • Benign failure modes • Hybrid devices: power conditioning, • storage

4. 54-inch Horizontal Axis Wind Turbine Electrical Output vs. Wind Speed, with 50 Ohm resistive load (2 tests)

5. Horizontal Axis Wind Turbine Simulation: Power Coefficient vs. Tip Speed Ratio

6. 40 30 20 10 10 20 30 40 Measured VAWT mechanical power in two tests vs. preliminary predictions from momentum streamtube theory.

7. Vt = - Vb Vertical Axis Wind Turbine, looking from above, showing relative velocity on the Advancing Blade Side, and the blade wake. Solidity, defined as diameter divided by blade chord times number of blades. As solidity increases, blade-wake interaction increases. So we need Multiple StreamTube Theory to account for power loss from streamtubes due to power extraction or drag due to blades

8. Aspect Ratio Effect on Optimal Tip Speed Ratio Blade element predictions of the mechanical power output of the 3-armed, bi-bladed VAWT, for different choices of blade chord compared to the baseline chord, with fixed span Baseline AR = Span/chord. ~9

9. Power coefficient vs. tip speed ratio for various solidities (Sandia data and simulation)

10. Comparison of (GT) and Sandia performance predictions at a solidity of 0.18.

11. Positive Torque (driving) occurs when net force has a positive component along the tangential direction, driving the blade Tangential coefficient vs. alpha for a NACA 0015 airfoil

12. Passive Starting Mechanisms Drag Channels • Enable startup in low winds • Provide some power • Limit performance at high • speeds Wind Guide Vanes • Passive control of local angle • of attack • Eliminate blade stall/negative torque • Allow self-starting To reach optimal TSR, one needs powered start

13. Conclusions Begun to integrate prediction, design and testing of a 2m x 2m vertical axis wind turbine with slanted double blades. Operating point predictions with multiple streamtube theory are validated against published results. Reynolds number effects are clearly seen in the predictions, and their proper inclusion allows the predictions to match experimental data well. Low performance at Tip Speed Ratio <1 is as per predictions. Simulation used to study how to eliminate negative torque at low tip speed ratio. A self-starting device using drag tubes isbeing simulated. Limiting turbine speed for safety implies that high tip speed ratio is best achieved at low wind speeds by taking the turbine to operating speed using human pedaling action or an electric motor. Time-resolved simulations and thus to control algorithms for adapting to given wind patterns and optimizing power extraction and safety.

14. ACKNOWLEDGEMENTS The work reported in this paper was made possible by resources being developed for the “EXTROVERT” cross-disciplinary learning project under NASA Grant NNX09AF67G S01. Mr. Anthony Springer is the Technical Monitor.