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EWEC 2007, MilanoMartin Geyler 1 Individual Blade Pitch Control Design for Load Reduction on Large Wind Turbines EWEC 2007 Milano, 7-10 May 2007 Martin.

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Presentation on theme: "EWEC 2007, MilanoMartin Geyler 1 Individual Blade Pitch Control Design for Load Reduction on Large Wind Turbines EWEC 2007 Milano, 7-10 May 2007 Martin."— Presentation transcript:

1 EWEC 2007, MilanoMartin Geyler 1 Individual Blade Pitch Control Design for Load Reduction on Large Wind Turbines EWEC 2007 Milano, 7-10 May 2007 Martin Geyler, Peter Caselitz Institut für Solare Energieversorgungstechnik (ISET e.V.) Telefon: +49-561-7294-364 e-mail: mgeyler@iset.uni-kassel.de

2 EWEC 2007, MilanoMartin Geyler 2 Tasks of Pitch Control (1) Basic Pitch Control Objectives: -Rotor speed control, -Limitation of power capture at high wind speeds  Collective Pitch Safety System: -Redundant aerodynamic brakes  Individual Pitch

3 EWEC 2007, MilanoMartin Geyler 3 Tasks of Pitch Control (2) Additional Objectives for Fatigue Load Reduction: -Suppression of 1p fluctuations in flapwise blade bending stress, -Compensation of yaw and tilt moments on nacelle (due to yaw misalignment, wind shear, turbulence)  Individual Pitch -Active damping of 1st axial tower bending mode  Collective Pitch

4 EWEC 2007, MilanoMartin Geyler 4 Control Design Objectives (Full Load Operation) At the presence of fluctuating aerodynamic forces acting on the rotor blades (due to turbulence, yaw misalignment etc.) the controller should act to: -Minimize deviation of rotor speed from rated speed  Disturbance rejection problem -Minimize tower top acceleration in the range of the first tower bending eigen frequency -Minimize 1p component in flapwise blade root bending moments (yaw and tilt moment compensation)

5 EWEC 2007, MilanoMartin Geyler 5 Control Design Limiting Conditions -Restrictions in pitch speed / acceleration -Rating of pitch drives, transmissions -Loading of blades -Avoid harmful interaction of pitch control with structural modes -Due to coupling between axial / tangential aerodynamic forces -speed control  1st axial tower bending mode -active tower damping  synchronous flapwise blade bending modes -yaw/tilt moment compensation  asynchronous flapwise blade bending modes -Robustness issues -Limited accuracy of model used for control design -Uncertainty / changes in aerodynamic coefficients over operating range  Bandwidth limitations for pitch control

6 EWEC 2007, MilanoMartin Geyler 6 Modular Control Design -Transparent structure w.r.t -parameter tuning, -output limitation, -All controllers act on pitch angles demand  strong coupling esp. between tower damping and speed control, -“One loop at a time” design approach: interactions between individual control loops may cause problems.

7 EWEC 2007, MilanoMartin Geyler 7 Multivariable Control Design General -Based on plant model to account for couplings between multiple inputs/outputs -All control loops are designed simultaneously. -Weighted optimisation criterion to account for several control objectives H  -Norm Minimisation Approach -Frequencies of disturbances are known: 1p, f Tower, f Blade.  Control objectives are conveniently formulated in the frequency domain by means of weighting functions. -Robustness requirements can be easily included into controller specification.

8 EWEC 2007, MilanoMartin Geyler 8 Linear Model for Multivariable Control Design Simplified model for coupled axial oscillations of tower top and blades MV control design requires simple, linear model of wind turbine including the relevant effects: Linearised Aerodynamics changes in -blade total thrust force, -blade flapwise aerodynamic moment, -blade edgewise aerodynamic moment, depending on changes in effective wind speed, rotor speed and pitch angle, Structural dynamics -turbine inertia -axial tower bending -flapwise blade bending

9 EWEC 2007, MilanoMartin Geyler 9 Parameter Identification Estimation of non-physical parameters of simplified structural dynamics model possible from measured / simulated time series of -tower top acceleration, -blade root bending moments, using LS methods. Parameter identification from simulated time series at 10% turbulence intensity Defined excitation -pitch angle changes, -snap-back cable Disturbances -turbulence influence, -numerical drift effects, can be minimised by appropriate filtering.

10 EWEC 2007, MilanoMartin Geyler 10 Integral MV Controller Structure -high order, low transparency of controller -reference values for indidividual blade pitch angles not divided into collective / cyclic components, which is desirable for limitation of pitch angle deviations and supervision -full load / part load transition requires switching of controllers

11 EWEC 2007, MilanoMartin Geyler 11 Decoupled MV Controller Structure Simplified turbine model can be divided into collective pitch / cyclic pitch models using a transformation  decoupled controller design Cyclic Pitch Controller:yaw and tilt moment compensation Collective Pitch Controller:speed control, active tower damping

12 EWEC 2007, MilanoMartin Geyler 12 Collective Pitch Control Design (1) Block scheme for collective pitch control design

13 EWEC 2007, MilanoMartin Geyler 13 Collective Pitch Control Design (2) Speed Control Active damping of axial tower oscillations Influence on 1st synchronous blade bending mode

14 EWEC 2007, MilanoMartin Geyler 14 Collective Pitch Control Design (3) Use of pitch angle weighting function Wp,0 1.Account for limits in pitch speed / pitch acceleration by limiting controller bandwidth 2.Ensure sufficient robustness against modelling uncertainty at higher frequencies max. singular value for nominal plant (blue) robust stability limit for max. singular value of additive perturbations (red) pitch angle weighting function (black)

15 EWEC 2007, MilanoMartin Geyler 15 Collective Pitch Control Design (4) Analysis of robustness against changes in aerodynamic coefficients for operational range 12 m/s < v Wind < 24 m/s

16 EWEC 2007, MilanoMartin Geyler 16 Cyclic Pitch Control Design (1) Block scheme for cyclic pitch control design

17 EWEC 2007, MilanoMartin Geyler 17 Cyclic Pitch Control Design (2) Open loop and closed loop transfer functions in the transformed system from disturbance (aerodynamic) yaw/tilt moment to measured yaw/tilt moment (derived from blade root bending moments) H  controller (red) PI controller (green)

18 EWEC 2007, MilanoMartin Geyler 18 Cyclic Pitch Control Design (3) Robustness to -variation in aerodynamic coefficients (low frequencies) -modelling uncertainty (high frequencies) robust stability limits for -H  controller (red) -PI controller (green) max. singular values for additive perturbations of nominal plant (blue) 12 m/s < v Wind < 24 m/s

19 EWEC 2007, MilanoMartin Geyler 19 Nonlinear Simulation (1) Detailed model of the wind turbine multi body model for description of wind turbine structural dynamics -Aerodynamics: -blade element method, -dynamic inflow model, -dynamic stall model, -aerodynamic damping -Structural dynamics: -Multi body model in 3D space, -yaw / tilt movement of nacelle, -oscillation direction of blades depending on pitch angle, -centrifugal stiffening -Pitch System: -detailed actuator model, -pitch gear teeth clearance, -blade bearing friction, -blade inertia around pitch axis depending on blade bending

20 EWEC 2007, MilanoMartin Geyler 20 v Wind,0 = 16 m/s tower top acceleration Nonlinear Simulation (2) Comparison of time series for baseline controller (blue ) / MV controller (red) Step on wind speed  v Wind = +1 m/s Step on wind direction  Wind = 15° flapwise blade root bending moment blade 1 rotor speed pitch angle blade 1

21 EWEC 2007, MilanoMartin Geyler 21 v Wind,0 = 12 m/s tower top acceleration Nonlinear Simulation (3) Comparison of time series for baseline controller (blue ) / MV controller (red) Step on wind speed  v Wind = +1 m/s Step on wind direction  Wind = 15° flapwise blade root bending moment blade 1 rotor speed pitch angle blade 1

22 EWEC 2007, MilanoMartin Geyler 22 v Wind,0 = 20 m/s tower top acceleration Nonlinear Simulation (4) Comparison of time series for baseline controller (blue ) / MV controller (red) Step on wind speed  v Wind = +1 m/s Step on wind direction  Wind = 15° flapwise blade root bending moment blade 1 rotor speed pitch angle blade 1

23 EWEC 2007, MilanoMartin Geyler 23 Hardware-in-the-Loop Test Bed

24 EWEC 2007, MilanoMartin Geyler 24 Results Hardware-in-the-Loop Test Bed (1) Comparison of time series for baseline controller (blue ) / MV controller (red) (Mean wind speed 15 m/s, Yaw misalignment 15°, Turbulence intensity 10%) rotor speed generator power pitch angle blade 1 pitch actuator torque blade 1 pitch actuator power blade 1

25 EWEC 2007, MilanoMartin Geyler 25 yaw / tilt moment compensation active tower damping Results Hardware-in-the-Loop Testbed (2) Comparison of amplitude spectra for baseline controller (blue ) / MV controller (red) (Mean wind speed 15 m/s, Yaw misalignment 15°, Turbulence intensity 10%) flapwise blade root bending moment blade 1 axial tower top acceleration pitch actuator torque blade 1

26 EWEC 2007, MilanoMartin Geyler 26 Summary / Outlook Summary -The pitch control problem with additional load reduction objectives is multivariable by nature. -Control design approach based on H  -Norm-Minimisation has been discussed, based on a simple linear model of the wind turbine. -Decoupled controllers can be designed for collective pitch (speed control, active tower damping) and cyclic pitch (yaw and tilt moment compensation). -The controllers show sufficient robustness to cover the entire full load operating region; robustness to modelling uncertainty can be easily adressed in the design approach. Outlook -Investigate performance limits of speed control. -Investigate gain scheduling.

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