Optimization and experimental validation of floating offshore wind turbines

1. Stuttgart Wind Energy (SWE)
@ Institute of Aircraft Design
Current research on
simulations of floating
offshore wind turbines
Ricardo Faerron, Frank Lemmer, Wei Yu,
Kolja Müller, Friedemann Borisade, Po Wen
Cheng
CADFEM 2017
Koblenz, Germany

2. Overview
• Wind Energy Research at University of Stuttgart
• Introduction to floating wind turbines
• Optimization of offshore wind turbine design from Lifes50 Plus Project
• Wave tank testing of floating Triple-Spar platform

3. Tradition
Ulrich Hütter: pioneer work on wind turbine design and GRP (1950s)
F.X. Wortmann: airfoil design, LWT (IAG)
Test site Schnittlingen: UNIWEX (ICA)
Endowed Chair of Wind Energy (SWE, since 2004)
Current Research Fields
• Testing and Measurement
• Conceptual Design and System Simulation
• Control, Optimization and Monitoring
• Aeroelasticity (IAG & SWE)
• Automated fibre composite
manufacturing techniques
• Aerodynamics and
aeroacoustics with CFD
• Airfoil design, wind tunnel tests
3
Wind Energy Research at the University of Stuttgart
• Multibody Dynamics
• Particle simulation
• Control Theory
• System Theory
IFB
ITMIST

4. 4
Main Research Fields
©DOTIGmbH
Testing and
Measurement
• Meteorological measurements
• LiDAR power curve, wake &
inflow meas.
• Floating Lidar
• Validation of fixed and floating
wind turbine simulations with
full-scale measurements
• wind/wave tank FOWT testing
Conceptual Design
and System Simulation
• Aero-Servo-Hydro-Elastic
MBS simulation of WT system
(on-/offshore/fixed/floating)
• Hydro-Elastic CFD-MBS
• Detailed Modelling of
subcomponents
• Code development
• Floating platform design
Control, Optimization
and Monitoring
• WITLIS toolbox
• Controller design
• Model predictive Control
• LiDAR feedforward
control
• Individual pitch control
• Wind farm control and
wake redirecting

5. 5
Introduction to floating wind turbines
"NewModelingToolAnalyzesFloatingPlatformConceptsforOffshoreWindTurbines,"U.S.
NationalRenewableEnergyLaboratory,NREL/FS-5000-50856,February2011

6. University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 6
Optimization and testing
Motivation
14 November
2017
 Large variation of current FOWT hull shapes
 Can optimization problem be formulated?
 Need for testing
GraphicbyJoshBauer,NREL,availableat:https://www.nrel.gov/news/program/2017/nrel-
market-report-finds-us-offshore-wind-industry-poised-multigigawatt-surge.html,

7. • Design standards for floating wind turbine require 1000s of loading cases with normal simulation
length of 3 hours
• High fidelity CFD analysis could be used for calculation of pressure and forces on a floating structure
but it is too time consuming
• Simplified models are needed which can accurately represent the dynamics of the floating structure as
well as the aeroelastics behaviour of the turbine.
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 7
Calculation of forces on the floating platform
14 November
2017

8. University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 8
Optimization of offshore wind
turbine design from Lifes50 Plus
Project
14 November
2017

9. OBJECTIVES
• Optimize and qualify to Technology Readiness Level (TRL) of 5, two innovative substructure designs
for 10MW turbines.
• Develop a streamlined and KPI (Key Performance Indicator) based methodology for the evaluation
and qualification process of floating substructures.
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design
9
Floating offshore wind for the future
Lifes50+ Project
1. www.nautilusfs.com
2. http://docslide.us/documents/oo-star-wind-floater-a-robust-and-
flexible-concept-for-floating-wind-trond-landbo-presentation-april-
2013.html
3. http://www.etrera2020.eu/component/phocadownload/category/2-
achivied-impacts.html?download=139:tlpwind-iberdrola-project
4. http://ideol-offshore.com
1 2 3 4

10. • Design space: small, three-column semi-
submersible platform
• Optimization problem: Reduce response to wind
and waves + costs
• Model-based optimal controller included
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 10
Goals
Optimization
14 November
2017
• [NREL]
"NewModelingToolAnalyzesFloatingPlatformConceptsforOffshoreWindTurbines,"U.S.
NationalRenewableEnergyLaboratory,NREL/FS-5000-50856,February2011

11. University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 11
Reference design turbine and platform
Set up of model
14 November
2017
• DTU 10MW turbine
• SWE-TripleSpar concrete foundation
(INNWIND.EU)
• Generic concept data available to
the research community at :
http://www.ifb.uni-
stuttgart.de/windenergie/downloads

12. University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 12
Design Space
14 November
2017
 Constraints:
 platform pitch angle ~3.5deg (-> determination of draft)
 max. draft ~60m
 min. space between heave plates

13. • Preliminary Ultimate Load State design
• As a function of free variables 𝑟, 𝑑
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 13
Interface steel tripod
Definition of design space
14 November
2017
Reference minimum spacing maximum spacing
[F. Amann]

14. • Several steps
• Structural design
• Hydrodynamic analysis of structure
• Controller optimization
• Time domain load analysis
• Outputs of the steps are fed into the
cost function
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 14
Optimization loop
14 November
2017

15. • In the optimization loop a Matlab based algorithm outputs hull shape parameters
• Parameters are read by APDL script
• The hull shape geometry is create within ANSYS APDL
• A routine modifies the input file for AQWA for the desired heading and wave frequencies
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 15
Mechanical APDL model
Creation of geometry
14 November
2017
Variables from Matlab
based optimization
algorithm
Updated variables
in APDL Script
APDL geometry –
Exported to
ANSYS AQWA

16. • ANSYS AQWA is used for calculation hydrodynamic parameters required for motion response
simulations in a radiation and diffraction analysis
• Uses potential flow theory to analyse the hydrodynamic behaviour of the floating structures
• Simulates linearized hydrodynamic fluid wave loading on floating bodies
• Analysis is frequency dependant
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 16
Hydrodynamic analysis with AQWA
14 November
2017
O.M.Faltinsen.SeaLoadsonShipsandOffshoreStructures,
CambridgeUniversityPress,ISBN0521458706,1990
Wave excitation loads Added mass
Damping and restoring
forces and moments

17. • Dynamic equilibrium equation for a floating body
• AQWA gives us results in the frequency domain
• The resulting output data that is used for modelling is:
• added mass matrix, (interpolated at the respective eigenfrequency Ac about the
platform center of mass)
• Wave excitation forces
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 17
Output of hydrodynamic analysis
14 November
2017
Added mass
Radiation damping
Stiffness matrix Wave excitation forces

18. • Calculation of wave excitation forces with AQWA results
• From frequency domain to time domain
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 18
Wave excitation forces
Output of hydrodynamic analysis
14 November
2017
Note: W(ω) represents the Fourier transform of a realization of a white Gaussian noise time series to
assure random phase of the spectrum
ω; wave frequency, β; wave direction, i; degree of freedom , t; time
Wave spectrum
Frequency dependant
wave forces from AQWA
Figure: Pressure distribution on
mesh of platform

19. • The Solver uses potential flow theory, thus:
• Depending on the element size of the surface mesh, a
maximum possible wave frequency can be determined
by AQWA.
• Potential flow calculations are the most time consuming
simulation within the optimization
• Mesh is therefore selected to be as coarse as possible,
still covering all important eigenfrequencies and wave
spectrum
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 19
Meshing for potential flow calculations
14 November
2017
Figure: Pressure distribution on
mesh of platform

20. University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 20
Optimization of controller and lifetime simulation of turbine
Simplified Low-Order Wind turbine model (SLOW)
14 November
2017
𝒒 =
𝑥 𝑝
𝑧 𝑝
𝛽 𝑝
𝑥 𝑡
Ω
• Flexible MBS, 5 DOFs
• Rotor as rigid disk, no
azimuth-dependency
• Quasi-steady aerodynamics,
scalar rotor-effective wind
speed
• No lateral motion
• No wave radiation model
• Linear wave excitation model
• Nonlinear mooring model
 Nonlinear + linearized formulation
 Good agreement with other models
𝒙 = 𝑨𝒙 + 𝑩𝑢

21. • Single-objective, non-gradient-based, constrained pattern search
• Cost functionals
• #1 Fatigue:
• #2 Fatigue and CAPEX:
*DEL: damage equivalent load
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 21
Optimizer
14 November
2017
 Fatigue vs. cost evaluation
𝐽 =
𝐷𝐸𝐿 − 𝐷𝐸𝐿 𝑚𝑎𝑥
𝐷𝐸𝐿 𝑚𝑎𝑥 − 𝐷𝐸𝐿 𝑚𝑖𝑛
𝐽 = 0.6
𝐷𝐸𝐿 − 𝐷𝐸𝐿 𝑚𝑎𝑥
𝐷𝐸𝐿 𝑚𝑎𝑥 − 𝐷𝐸𝐿 𝑚𝑖𝑛
+
€ − € 𝑚𝑎𝑥
€ 𝑚𝑎𝑥 − € 𝑚𝑖𝑛

22. • Several steps
• Structural design
• Hydrodynamic analysis of structure
• Controller optimization
• Time domain load analysis
• Outputs of the steps are fed into the
cost function
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 22
Reminder of the optimization
Optimization loop
14 November
2017

23. Run #1 Run #2
cost functional f(DEL) f(DEL, CAPEX)
column spacing [m] 22.14 24.0
column radius [m] 10.0 10.0
heave plate radius [m] 17.0 10.0
heave plate thickness [m] 9.73 -
CAPEX [M€] 12.1 9.4
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 23
Results (1)
14 November
2017

24. University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 24
Results (2)
14 November
2017
 Wave cancellation
 At expense of higher material cost
 The optimum is somewhere in between!
result #2 (DEL+CAPEX)
result #1 (DEL)
𝐷𝐸𝐿 𝑚𝑎𝑥
wind
waves
tower-
top disp.
rotor
speed
ptfm.
pitch
disp.

25. University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 25
From optimization to testing:
Wave tank testing of Triple-Spar
platform
14 November
2017

26. • Model tests require scaling methodology of the aerodynamic
forces.
• Due to the complexity, past tests have not included pitch
control of the blades
• Components
• Wind model turbine constructed at the Danish Technical
University
• Floating platform constructed at the SWE at the University
of Stuttgart
• Testing at DHI Denmark
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 26
Introduction
Wave tank testing of Triple-Spar platform
14 November
2017
1:60 scaled DTU 10MW
reference wind turbine

27. • Validation of SLOW (simplified low-order simulation model) including aerodynamics,
hydrodynamics, mooring dynamics and structural dynamics
• Implementation of real-time blade-pitch control system on a scaled model in a combined
wind-and-wave tank
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 27
Goals
Wave tank testing of Triple-Spar platform
14 November
2017
1:60 scaled DTU 10MW reference wind turbine SLOW model

28. University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 28
Instability of floating wind turbine
Importance of estimation of damping and added mass
14 November
2017
G.vanderVeen,I.Couchman,R.Bowyer.Controloffloatingwindturbines,
AmericanControlConference(ACC),Canada,2011
 Controller should be design to avoid instability

29. University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 29
Instability of floating wind turbine
Importance of estimation of damping and added mass
14 November
2017
𝛽 𝑃 : platform-pitch displacement
𝑀55 : total structural moment of
inertia (platform, rotor and tower
together are regarded as one rigid-
body),
𝐴55 : added inertia (from added
mass),
𝐵55 : radiation damping and
linearized viscous damping,
𝐶55 : linearized pitch restoring
stiffness from hydrostatics and
mooring lines
𝐹𝑎 : aerodynamic thrust
𝐿 𝑇 : hub height
V: wind speed
𝜔 𝑛 = 𝐶55/(𝑀55 + 𝐴55)
𝜁 =
(𝐵55 +
𝜕𝐹𝑎
𝜕𝑉
𝐿 𝑇
2
)
2 𝐶55 ∙ (𝑀55 + 𝐴55)
In pitch direction the system is a
second-order system
Damping, stiffness and
added mass are output
from AQWA into
simulation model
Controller design based
on hydrodynamic
parameters helps avoid
excitation

30. • Hydrodynamic parameters and wave forces calculated with ANSYS AQWA are used as
inputs for simulations in SLOW models for optimization of floating wind turbines
• Interface is created allowing communication between the Matlab based optimizer, APDL
and AQWA
• Knowledge of the hydrodynamic properties of the floating platform allows for appropriate
design of the turbine controller in order to avoid unwanted instabilities in the system
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 30
Summary
14 November
2017

31. • Hydrodynamic analysis tools are needed for the analysis of the load response for the
development of future floating offshore wind turbine platforms
• As new ideas and concepts for floating offshore wind turbines arise, simulation software
needs to provide accurate hydrodynamic parameters for estimation of the dynamic
responses
• Integration of the hydrodynamic solvers with the aeroelastic solvers is still a current field
of research for floating wind turbines
University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 31
Outlook
14 November
2017

32. References
F. Lemmer, K. Müller, W. Yu, R. Faerron Guzmán, M. Kretschmer. Deliverable: 4.3 Optimization
framework and methodology for optimized floater design. University of Stuttgart. Technical report for
Horizon 2020 LIFES50+ Project. 2017
Yu, W., Lemmer, F., Bredmose, H., Borg, M., Pegalajar-Jurado, A., Mikkelsen, R.F., Larsen, T.S.,
Fjelstrup, T., Lomholt, A.K., Boehm, L., Schlipf, D., Azcona, J.A. The TripleSpar campaign:
Implementation and test of a blade pitch controller on a scaled floating wind turbine model. Energy
Procedia. (2017). (to be published)
14.11.2017 32

33. University of Stuttgart, Stuttgart Wind Energy (SWE) @ Institute of Aircraft Design 33
Example of pressure distribution
14 November
2017
 FK-pressure, regular wave, 𝑇𝑝 = 9s

34. e-mail
phone +49 (0) 711 685-
fax +49 (0) 711 685-
University of Stuttgart
Thank you for
your attention
Ricardo Faerron
68332
Stuttgart Wind Energy (SWE)
faerron@ifb.uni-stuttgart.de
Acknowledgements
• The research leading to these results
has received funding from the
European Union’s Horizon 2020
research and innovation programme
under grant agreement No. 640741
(LIFES50+). The support is highly
appreciated.
• This research was done in
collaboration with www.sowento.com ,
a spin-off for floating wind and LiDAR-
based control solutions.