EWEC 2006, Athens Martin Geyler

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Hardware-in-the-Loop Development and Testing of New Pitch Control Algorithms

EWEC 2006 Athens

Martin Geyler, Jochen Giebhardt, Bahram PanahandehInstitut für Solare Energieversorgungstechnik (ISET e.V.)Phone: +49-561-7294-364e-mail: mgeyler@iset.uni-kassel.de

EWEC 2006, Athens Martin Geyler

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Project Objectives

- Individual blade pitch control- compensation for unsymmetrical

inflow conditions due to turbulence or deterministic effects

- active damping for tower and blades

Project PartnersDevelopment of advanced pitch control algorithms for load reduction in large wind turbines

- Modular controller design

- Development of safety algorithms- stability monitoring, - handling of sensor faults

- Identification of requirements for the pitch system using a Hardware-in-the-Loop test bed setup

- dynamics, - loads, wear, - power consumption, thermal

losses,- load sensors- communication requirements

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Control Problem

Schematic of Control Loop

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Test Bed: Schematic Overview

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Test Bed: Control Concept

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Test Bed: Laboratory Setup

Load DriveInverter Cabinet

Pitch DriveInverter Cabinet

Pitch Motors

Load Machines

Controller Rack with Simulation PCs

Host PC

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Block structure of Simulink model

Real-Time Simulation: Overall Wind Turbine Model

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- 14 rigid bodies connected by joints:(1) Universal joints with torsional stiffness

and damping representing flexibility of the structure

(2) Revolute joints with external torque input representing actuators

Mechanical model

Real-Time Simulation: Mechanical Model (1)

- fully recursive algorithm: „Method of Articulated Inertia“:

- tree-like structure is exploited- avoids need for inverting large mass

matrices- O(N) method: computational effort

increases linearly with number of DOF- Mass forces (gravity, inertia) inherently

included by the algorithm.

- Solver: 3rd-order Runge-Kutta solver at 1ms time step

- ca. 450 µs calculation time on Athlon 4000+ PC

Multibody approach:

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Mechanical model

Real-Time Simulation: Mechanical Model (2)

- Parameters for multi body model were calculated using a optimisation algorithm to find a best fit to a given finite elements (FE) model:

1st mode and static deflection of simplified blade model with 2 rigid sections;Comparison with FE model

1. Step: Optimisation of joint locations in order to allow for best representation of first 3 mode shapes2. Step: Optimisation of stiffness parameters and joint twist angles in order to fit eigen frequencies and mode shapes

- Validation: Comparison of static deflection due to a constant line load (blade) or constant tower top force

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Load torque reference values for load drives will include the following effects:

Example simulation for pitch load situation in turbulent wind conditions

Real-Time Simulation: Pitch System Model

- pitch gear ratio 1:1000

- tooth clearance at fast side of pitch gears

- blade bearing friction - DRE/CON-formula for large

bearings: MR = µD/2 * k * M blade

root

- Four point contact bearings: µD = 0.006, k = 4.37

- Components for axial and radial force have been neglected.

- changing inertia due to blade deflection inherently included by mechanical model

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Real-Time Simulation: Aerodynamic Model (1)

- Blade Element Momentum Theory (BEM)- 12 blade elements per blade

- semi-empirical corrections: state-of-the-art implementation of

- dynamic inflow- yawed inflow- dynamic stall

- total 240 aerodynamic states

- Solver: simple Forward-Euler integration at 1ms time stepcalculation time ca. 45 µs on Athlon 4000+ PC

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Dynamic Inflow Model (ECN):- Local inflow condition at blade sections depend on free wind

speed and load situation of the rotor in a dynamic manner.

- Example: Overshoot in blade root bending moment for fast step on pitch angle

Simulation Tjaereborg Experiment

Real-Time Simulation: Aerodynamic Model (2)

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Dynamic Stall Model (Beddoes-Leishmann-Type):- Effect: dynamic lift forces can be considerable bigger than

predicted by stationary cL--curve for fast changes in pitch angle.

Simulation Measurement (Risø)

Real-Time Simulation: Aerodynamic Model (3)

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2-D turbulent Wind Field is simulated off-line and read from a file during real time simulation reproducible time series- 8 x 8 points in the rotor plane, - linear interpolation- only mean wind direction

Real-Time Simulation: Turbulent Wind Field Input (1)

Method by Mann - wind field is assembled in a 3D-box by means of inverse

FFT- Fourier Coefficients calculated from spectral-tensor

( only 11 used )- „frozen turbulence“ : dimension L1 is used as time axisParameter fitting to Kaimal spectrum

Input parameters: - mean wind speed, - mean wind shear, - turbulence intensity

Extreme gust events can be embedded into stochastic turbulent wind field:

- Most likely gust shape calculated from correlation matrix R and a given criterion e.g. total jump in wind speed at given location

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Real-Time Simulation: Turbulent Wind Field Input (2)

Averaged auto-power spectrum for simulated wind fields

Example for extreme gust eventCriterion: v = 10 m/s, t = 16 s, location

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- 3D visualisation tool for motion and load situation of simulated wind turbine

- VRML based

- Visualisation coupled to real-time simulation via TCP/IP based communication channel

Visualisation with VRML

Real-Time Simulation: Visualisation

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First Results (1)

- Algorithm for yaw and tilt moment compensation implemented and tested

simulated reduction in 1p component of flapwise blade root bending moment

- (simulated) 1p component in flapwise blade root bending moments is almost cancelled,

- pitch drive rating seems sufficient for producing required 1p cyclic pitch offsets, however, considerably increased motion as compared to normal collective pitch operation- simple fuzzy scheme for supervision and controller gain adjustment

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First Results (2)

Measurement of Pitch Drive Load Torques

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Conclusions

- Hardware-in-the-Loop test bed for Pitch Drives has been developed and successfully taken into operation.

- Real-Time Simulation Environment allows for providing realistic load conditions as well as all required feedback signals to the tested Pitch Control System.

- First simulation results and measurements for a Yaw- and Tilt-Moment Compensation Controller (Proof-Of-Concept).

- It is believed, that the test bed will greatly improve the understanding of the system aspects of advanced pitch control strategies.

Thank You.