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1 Hazim Namik Department of Mechanical Engineering Deepwater Floating Offshore Wind Turbine Control Methods

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Deepwater Floating Offshore Wind Turbine Control Methods. Hazim Namik Department of Mechanical Engineering. Outline. Introduction to wind turbines Offshore wind turbines Wind resource Floating wind turbines Control Methods Summary. Introduction. - PowerPoint PPT Presentation

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Page 1: Hazim Namik Department of Mechanical Engineering

1

Hazim NamikDepartment of Mechanical Engineering

Deepwater Floating Offshore Wind Turbine Control Methods

Page 2: Hazim Namik Department of Mechanical Engineering

2

Outline

• Introduction to wind turbines

• Offshore wind turbines– Wind resource– Floating wind turbines

• Control Methods

• Summary

Page 3: Hazim Namik Department of Mechanical Engineering

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Introduction

• Wind energy is the fastest growing renewable energy

• Wind energy is a form of solar energy– Only 2% of received solar energy is converted

to wind

• Wind turbines convert some of the wind energy to useful mechanical energy

Page 4: Hazim Namik Department of Mechanical Engineering

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Types of Wind Turbines

• Two main types of wind turbines (WTs)– Vertical axis (VAWT)– Horizontal axis (HAWT)

• HAWT are generally more efficient, hence used for power generation

Page 5: Hazim Namik Department of Mechanical Engineering

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Major Components• Blades• Hub• Nacelle

• High speed and low speed shafts

• Gearbox• Generator

• Yaw drive system

Source: US Dept. of Energy

Page 6: Hazim Namik Department of Mechanical Engineering

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Offshore vs. Onshore Winds

• Advantages:– Stronger and steadier winds– Have less turbulence– Have less vertical shear– Winds are more spatially consistent

• Disadvantages– The winds Interact with waves– Offshore winds are harder to measure

Page 7: Hazim Namik Department of Mechanical Engineering

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Vertical Shear

• Surface roughness at sea is lower; therefore, higher wind speeds at lower heights.

Source: Wind Turbines, Erich Hau

Page 8: Hazim Namik Department of Mechanical Engineering

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Offshore Resource Availability

Source: Goldman, P., Offshore Wind Energy, in Workshop on Deep Water Offshore Wind Energy Systems. 2003, Department of Energy.

Page 9: Hazim Namik Department of Mechanical Engineering

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Going Further Offshore

Source: OCS Alternative Energy and Alternate Use Programmatic EIShttp://ocsenergy.anl.gov/guide/wind/index.cfm

Page 10: Hazim Namik Department of Mechanical Engineering

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Deepwater Floating Wind Turbines

Source: Jonkman, J. Development and Verification of a Fully Coupled Simulator for Offshore Wind Turbines

Page 11: Hazim Namik Department of Mechanical Engineering

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NREL 5MW Wind Turbine• Barge floating platform

• 5MW power rating

• 126m diameter rotor (3 Blades)

• 90m hub height

• 153m tall

Source: Jonkman, J.M., Dynamics Modeling and Loads Analysis of an Offshore Floating Wind Turbine, in Department of Aerospace Engineering Sciences. 2007, University of Colorado: Boulder, Colorado, USA (to be published).

Source: http://www.mlg.org.au/visual.htm

RePower 5MW, 126m diameter rotorSource: RE UK

Page 12: Hazim Namik Department of Mechanical Engineering

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General Turbine Control Methods

Collective Pitch

Individual Pitch

Pitch to Feather

Pitch to Stall

Control Options

Blade Pitch Generator Torque

Mode of Operation

Principle of Operation

Page 13: Hazim Namik Department of Mechanical Engineering

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Floating Turbine Control Methodology

Simple Onshore Baseline controller

Complex Onshore

Special Offshore

Page 14: Hazim Namik Department of Mechanical Engineering

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Baseline Controller Overview

• Generator torque controller – Maximum power below rated wind speed– Regulate power above rated

• Collective pitch controller– Regulate generator speed above rated wind

speed

Page 15: Hazim Namik Department of Mechanical Engineering

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Platform Pitching – Problem

• Factors affecting platform pitching– Ocean waves

– Aerodynamic thrust

– Mooring lines

Page 16: Hazim Namik Department of Mechanical Engineering

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Modifications to the Baseline Controller• Tower feedback loop

– Additional blade pitch controller– Tower top acceleration feedback

• Active pitch to stall– Extra thrust force when blade is stalled may reduce

platform pitching

• Detuned controller gains– Reduced pitch to feather controller gains

Source: Jonkman, J.M., Dynamics Modeling and Loads Analysis of an Offshore Floating Wind Turbine, in Department of Aerospace Engineering Sciences. 2007, University of Colorado: Boulder, Colorado, USA (to be published).

Page 17: Hazim Namik Department of Mechanical Engineering

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Results – Tower Feedback

• Poor power regulation

• Marginally reduced platform pitching

Source: Jonkman, J.M., Dynamics Modeling and Loads Analysis of an Offshore Floating Wind Turbine, in Department of Aerospace Engineering Sciences. 2007, University of Colorado: Boulder, Colorado, USA (to be published).

Page 18: Hazim Namik Department of Mechanical Engineering

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Results – Pitch to Stall

• Excellent power regulation

• Large platform oscillations

Source: Jonkman, J.M., Dynamics Modeling and Loads Analysis of an Offshore Floating Wind Turbine, in Department of Aerospace Engineering Sciences. 2007, University of Colorado: Boulder, Colorado, USA (to be published).

Page 19: Hazim Namik Department of Mechanical Engineering

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Results – Detuned Gains

• Reasonable power regulation

• Reduced platform pitching – but not enough

Source: Jonkman, J.M., Dynamics Modeling and Loads Analysis of an Offshore Floating Wind Turbine, in Department of Aerospace Engineering Sciences. 2007, University of Colorado: Boulder, Colorado, USA (to be published).

Page 20: Hazim Namik Department of Mechanical Engineering

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Floating Turbine Control Methodology

Simple Onshore Baseline controller

Complex Onshore

Special Offshore

State space with individual blade pitch

Nonlinear with individual blade pitch

Without adding any actuators

Adding necessary actuators

Current State of Research Worldwide

Cla

ssic

al

Con

trol

Mod

ern

Con

trol

Page 21: Hazim Namik Department of Mechanical Engineering

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Summary• Offshore winds are stronger and steadier than

onshore winds

• Floating turbines are economically feasible for deep waters

• Classical control was not successful at controlling a floating wind turbine

• Modern control with state space or nonlinear control is the way to go

Page 22: Hazim Namik Department of Mechanical Engineering

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Thank you

Page 23: Hazim Namik Department of Mechanical Engineering

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Water Depths

% of Water Depths in Different Regions up to 100km Offshore

RegionWater Depth

<25m 25-50m 50-100m 100-300m

North Europe 21 26 32 20South Europe 16 11 23 49Japan 22 9 18 51USA 50 26 13 11

Source: Henderson, A.R., Support Structures for Floating Offshore Windfarms, in Workshop on Deep Water Offshore Wind Energy Systems. 2003, Department of Energy.

Page 24: Hazim Namik Department of Mechanical Engineering

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Floating Wind Turbines

• Reduce the cost of construction for deep waters

• Can be located close to major demand centres

• Could interfere with aerial and naval navigation

• Harder to control as added dynamics of platform motion affect performance

Page 25: Hazim Namik Department of Mechanical Engineering

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Power Regions

• Region 1– No power is generated

below the cut in speed• Region 2

– Maximise power capture

• Region 3– Regulate to the rated

power

Page 26: Hazim Namik Department of Mechanical Engineering

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Torque Controller

• Region 1

• Region 2

• Region 3

• Regions 1.5 and 2.5 are linear transitions between the regions

2HSSGen KT

0GenT

HSSGen

RatedGen

PT

Page 27: Hazim Namik Department of Mechanical Engineering

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Applied Generator Torque

0

5

10

15

20

25

30

35

40

45

0 500 1000 1500

Thou

sand

s

High Speed Shaft Speed (rpm)

Gen

erat

or T

orqu

e (N

m) Tg_rated (Nm)

Tg_r1 (Nm)

Tg_r1.5 (Nm)

Tg_r2 (Nm)

Tg_r2.5 (Nm)

Tg_r3 (Nm)

T=Kw 2̂

Torque Controller

Reg

ion

1.0

Reg

ion

1.5

Reg

ion

2.0

Reg

ion

3.0

Region 2.5

Page 28: Hazim Namik Department of Mechanical Engineering

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Collective Pitch Controller

• PI Controller to regulate generator speed• Controller gains calculated according to

the design parameters– ωn = 0.7 rad/s and ζ = 0.7

• Simple DOF model with PI controller gives

PN

IKand

PN

IK

Gear

nratedRotorDrivetrainI

Gear

nratedRotorDrivetrainP

2,,2

Page 29: Hazim Namik Department of Mechanical Engineering

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Pitch Sensitivity

• Power sensitivity to blade pitch is found through linearization of the turbine model

DxCPBxAx

Model Space State Linearized

• Pitch sensitivity varies almost linearly with blade pitch

• Gain Scheduled PI gains are calculated based on blade pitch through a gain correction factor GK(θ)

Page 30: Hazim Namik Department of Mechanical Engineering

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Gain Scheduled PI GainsGain Scheduled PID Controller

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

0 5 10 15 20 25

Pitch (deg)

Corr

ectio

n Fa

ctor

KP(θ)

KI(θ)

Page 31: Hazim Namik Department of Mechanical Engineering

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Baseline Controller in SIMULINK

FAST Engine

Data Extraction and Plotting

Controllers

Page 32: Hazim Namik Department of Mechanical Engineering

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Region 2 Torque Gain Derivation

RotRotP TPVRAVCP and,

21 3

23

5

23

223

2

121

21

21

RotP

Rot

RotPRot

PPRot

RCT

RRCT

RVRCVRAVCT

Page 33: Hazim Namik Department of Mechanical Engineering

33

33

532

3

22

3

5

1800cos

1302

cos

Gear

PHSSGen

GearHSS

PGen

NRCKandKT

NRCT

R2 Torque Gain Derivation Cont.

• Changing to generator torque and HSS speed in rpm and taking pre-cone into account

• In Region 2, CP = CP,Max and λ = λo

• For this Turbine:– CP,Max= 0.482, λo= 7.55, R= 63m, α=2.5°, and NGear=

97

Page 34: Hazim Namik Department of Mechanical Engineering

34

23

53

1800cos

RotP

RotRCT

Why N3

• At steady state TGen = THSS

2233

53

2

3

53

1800cos

1800cos

HSSGenHSSGear

PGen

Gear

HSSPGen

Gear

HSSRot

Gear

RotGen

KTN

RCT

NNRCT

NAnd

NTT

Page 35: Hazim Namik Department of Mechanical Engineering

35

Pitch Controller Derivation

• Single DOF model of the turbine drivetrain gives

DrivetrainGenGearRotorGenGearAero IdtdINITNT 0

2

• Taylor approximation of aerodynamic and generator torques gives

PPT

NP

NPT

Aero

GearGearGen

00

0

20

0

0

0

1

Page 36: Hazim Namik Department of Mechanical Engineering

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Pitch Controller Derivation (Contd.)

• Pitch commands (Δθ) comes from the PID controller equation

GearD

t

GearIGearP NKdtNKNK0

• By making the following substitution and replacing everything in the equation of motion, we get

0111

000

K

IGear

C

PGear

M

DGearDrivetrain KNPKNPKNPI

Page 37: Hazim Namik Department of Mechanical Engineering

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Pitch Controller Derivation (Contd.)

• This is a 2nd order differential equation

• Expanding ωn and ζ and solving for a PI controller (KD = 0) gives

nn

K

IGear

C

PGear

M

DGearDrivetrain

MC

andMK

KNPKNPKNPI

2

0111

000

PN

IKand

PN

IK

Gear

nDrivetrainI

Gear

nDrivetrainP

2002