Optimal Rotors for Distributed Wind Turbines

1. Optimal Rotors for Distributed Wind Turbines

2. Overview • Why small wind turbines? • Why are they interesting academically? • Design approach • Study results

3. There is wind out there if you’re careful where to look • Wind resource • Studies of wind in urban areas • Generally low mean wind speeds • Turbulence • Some viable locations • Purposeful building integration • Windy locales • Remote locations • Open terrain • Higher energy costs • Tower mounted preferable

4. The top of a 100m pole is always going have better wind, but... • MW scale machines are hard to beat • Economies of scale • Wind shear • kW scale machines left in the past? • MW lessons learnt not applied to small machines • Consumer demand • Engagement with energy source • Distributed energy source • Transmission infrastructure • Smart grids

5. There is unique academic value at the small scale • Validation data & trying new ideas are easy • Design-build-test for low $ • Challenging design space • Strive for multi-objective, multi-disciplinary optimum • Energy yield, cost, noise, etc. • Shape, structure, etc. • Matching generator to rotor • Tools & methods applicable at all scales

6. And of course someone has pay the bills! • Industrial sponsor • Ampair in UK • Redesigning & up-scaling product range • 100 W – 8 kW • Some units left off results for commercial sensitivities • UVic efforts • Focusing on rotor blade design • HAWTs not VAWTs

7. So, what’s different at the small scale? • Reynolds number • Operating around transition • Rotor control • Controlled pitching too expensive • Failsafe pitching possible (PTS or PTF) • Generator • Cogging torque • Startup wind speed • Power electronics • Full power conversion • Passive or active generator torque control

8. Our approach to rotor optimization • A stepwise approach

9. BEM-based analysis tool ExcelBEM was used for analysis • Implementation • Excel interface • Underlying C/Matlab code • Enhanced BEM method • Coned rotors, including blade section sweep • Steady and unsteady aero • Rigid body blade flapping • Implicit optimal control algorithms • PTF, PTS, VSS • Generator characteristics • Blade section structural properties & stresses • Low frequency noise

10. The blade shape is parameterized with DVs control points of Bezier curves • Incorporate implicit shape constraints • E.g. parabolic tip • Convex hull property

11. Blade section choice treated as a parameter • Want to be confident in aerodynamic properties • Not much experimental data available! • Eppler & NACA 44XX • Flat plate extensions for full AOA range • Structure • Glass/carbon thermoplastic skins (Twintex) • Foam core

12. The generator characteristic is a parameter • Passive PE • Single torque-speed-power relationship • Torque matching problem • Over speed protection from centrifugal PTS • E.g. battery charging • Active PE • Variable speed by varying generator load on rotor • Torque-speed-power surface • Need to find optimum operating profile on surface • Variable efficiency • Not sufficient to find optimal tip-speed ratio

13. Generator and aerodynamic torque must be equal for passive PE • Example of a bad match!

14. Two approaches to active PE optimization • Implicit • Use built-in optimal operating routines in ExcelBEM • No extra DVs • Computationally intensive • Require multiple BEM solutions for each design iterate • Explicit • Add DVs for Ω at 15-20 wind speeds • Directly control rotor speeds • Extra finite differencing, but better overall

15. The overall optimization procedure was developed during the study • Full process only applied to final example • Incremental steps for other design cases • Final design/optimization process • Matlab driven interactive with designer • Navigate towards energy yield optimum • Pick airfoil set • Analytic chord/twist optimum for CP at given λopt • Fit shape DVs to analytic optimum (lsqnonlin) • Direct numerical optimization for Eann over entire wind speed range (fmincon) • Careful numerics • Finite differencing (round off & truncation errors) • Limit step sizes

16. Additional constraints can be applied to the optimization • Startup wind speed • Cogging torque must be overcome • Either: • Specify Vcut-in (no extra DVs) • Add Vcut-in as a DV and avoid over constraining • Maximum electrical power • Geometric constraints for manufacture • Max. chord and twist • Others possible, but not used here • E.g. tip speed (noise), tower thrust

17. Additional step for structure definition • Manual iteration on ply count (1-4) for one of two cases: • Simulated loading: extreme storm & rated operation • IEC 61400-2: root bending moments at various conditions • Scaled loading for other sections • Found that maximum yaw rate tends to limit • Eventually like to couple aero-structure • Not as critical at small scale

18. Design studies • Predetermined diameters/powers

19. Ampair 600 rotor redesign • First design • No generator characteristic available • Only guesses at rotor speeds at cut-in and rated power • Assumption that pitch mechanism activates just after rated power • Could not perform Eann optimization directly • Numerical optimization for CP • Range of λopt tried • 6 found as optimum structurally and aerodynamically

20. Field tests were carried out on new rotor yielding a few insights • Clearly require good generator spec. • Pitching mechanism performance also related • Should be considering dynamic operation

21. Ampair 300 rotor redesign • Well characterized generator • Passive PE • Full Eann optimizer not yet available • Could now redo and impose torque matching constraint • Numerical CP optimization • Range of λopt tried • Post-process • Implicit torque matchingroutines • Identify rotor with highestenergy yield

22. Fairly good rotor match to generator • Generator still a bit aggressive • Better if generator curve shifted left

23. Imposition of cogging constraint changes rotor somewhat • Effects • Larger chords • Startup now at 3m/s, vs. 5m/s for unconstrained design • Generator more aggressive relative to rotor

24. A unique test apparatus was available… • Equipment • Modified VW golf • 12V load • Anemometer, tachometer, etc. • Quiet UK country lane • Windless day • Repeated/averaged runs

25. Constant speed testing atop vehicle performed for verification • Quite good agreement! • Not just aerodynamics being tested • Results include generator matching algorithm

26. 6000 W clean sheet design • Full Eann optimizer available • Active PE • Variable speed • Optimal power capture • VSS control above rated • Generator characteristic contrived for these results • Data from dynamometer is being gathered • Expect efficiency degradation with partial power • Assume 70%-95% performance

27. Generator characteristic defined from “experimental” data points

28. Begin with simple analytic CP optimum and fit blade profiles with chord constraint • Test range of λopt • Implicit optimal operation algorithm • Optimum around λ = 5-6 • Performance hit with simple fitting procedure

29. Perform full Eann optimization with increasing cogging torque constraint • Blade profiles

30. Operating curves

31. Performance over generator map Note high cogging torque forhigher solidity rotors

32. Cogging torque impacts energy yield • Key results • Complete optimization process is superior to simple chord cap of a CP optimized blade • Shape changes predominantly in the chord profiles • Some twist to maintain optimal angles of attack • Increasing cogging torque constraint leads to: • Higher solidity rotors • Attendant structural and weight repercussions

33. Acoustic concerns over downwind rotor led to study of coning angle/offset • Design point • Rated conditions (11m/s)

34. A compromise of 7° was reached between acoustics and stress • Centrifugal moments build past 7°

35. Future directions • More integration in MDO loop • Concurrent structures optimization • Generator/PE design • Add DVs and constraints • Optimal blade lengths? • Tower thrust tradeoffs • Include dynamic behavior • Stochastic winds • Effect on power curve • Fatigue loads?

36. Thanks are in order… UVic Engineering Design Office