Frederik Zahle - Design of an Aeroelastically Tailored 10 MW Wind Turbine Rotor

Design of an Aeroelastically Tailored 10 MW Wind TurbineRotor

Frederik Zahle, Carlo Tibaldi, Christian Pavese, Michael K.McWilliam, Jose P. A. A. Blasques, Morten H. Hansen

Wind Energy DepartmentTechnical University of Denmark

Sandia Wind Turbine Blade Workshop30 August to 1 September 2016

Albuquerque, NM, USA

IntroductionBlade Design Trade-Offs

A key challenge in blade design is the trade-off between aerodynamics (AEP)

on one side vs. mass and loads on the other side.

2 of 24F Zahle et al.Wind Energy Department · DTU Design of an Aeroelastically Tailored Rotor


Introducing new blade design technologies and design tools can help us push

these barriers, increasing AEP and reducing costs.



� A blade designer has to

understand the complex

couplings between the design

variables (Dv), the constraints

(Cn) and the objective(s) (Obj).

� Parameter/sensitivity studies can

help understand relations

between key parameters.

� With potentially hundreds of

design variables, it can be

extremely challenging to

understand all the outputs.

� Numerical optimization is

necessary to carry out

multidisciplinary design.


IntroductionProjects

� DTU Wind Energy participates in many Danish and European researchprojects focused on development of design solutions of future windturbines:

� Stretched Rotor: Collaboration between DTU Wind Energy and LM WindPower to apply multidisciplinary optimization to stretch a 3.2 MW rotorwithout increasing its loads envelope (Sponsored by Danish EnergyAgency).

� INDUFLAP2: Collaboration with Siemens and Rehau to develop anddemonstrate an active flap system for load alleviation (Sponsored by DanishEnergy Agency).

� INNWIND.eu: Development of cost effective design solutions for 10 MW to20 MW offshore turbines (EU sponsored).

� AVATAR: Development and validation of advanced aerodynamic models fornext generation large scale turbines (EU sponsored).


IntroductionThis Presentation

� This work presents an integrated multidisciplinary wind turbine

optimization framework utilizing state-of-the-art aeroelastic and strutural

tools.

� Simultaneous design of the outer geometry and internal structure of the

blade,

� The framework is utilized to design a 10 MW rotor constrained not to

exceed the design loads and mass of the DTU 10 MW Reference Wind

Turbine.


Multidisciplinary Design FrameworkHawtOpt2: Tool for Aero-servo-elastic Optimization ofWind Turbines

HawtOpt2 provides workflows that coupleaeroelastic and structural solvers together toallow for:

� Simultaneous and fully coupledoptimization of lofted blade shape and thestructural design of a blade.

� Exploration of the many often conflictingobjectives and constraints in a rotordesign.

� Detailed tailoring of aerodynamic andstructural properties.

� Constraints on specific fatigue damageloads.

� Placement of natural frequencies.


Multidisciplinary Design FrameworkHawtOpt2: Tool for Aero-servo-elastic Optimization ofWind Turbines

� Underlying framework: OpenMDAO(written in Python),

� Optimization algorithm: IPOPT interfacedthrough PyOptSparse,

� Geometric parameterisation:FUSED-Wind,

� HAWCStab2/HAWC2 interface:

� AEP,

� Frequency placement,

� Fatigue in frequency domain,

� Reduced/full DLB in time domain,

� BECAS interface:

� Calculation of stiffness properties,

� Calculation of material failure andfatigue damage.


Multidisciplinary Design FrameworkAero-elastic Solvers: HAWCStab2 and HAWC2

� Structural model: geometrically

non-linear Timoshenko finite

beam element model.

� Aerodynamic model: unsteady

BEM including effects of shed

vorticity and dynamic stall and

dynamic inflow.

� HAWCStab2: Analytic

linearization around an

aero-structural steady state

ignoring gravitational forces.

� HAWCStab2: Fatigue damage

calculated in frequency domain

(including effect of ATEFs) based

on the linear model computed by

HAWCStab2.Image from: Sønderby and Hansen, Wind Energy, 2014


Multidisciplinary Design FrameworkStructural Solver: BECAS (BEam Cross section AnalysisSoftware)

� Finite element based tool for

analysis of the stiffness and

mass properties of beam

cross sections.

� Correctly predicts effects

stemming from material

anisotropy and inhomogeneity

in sections of arbitrary

geometry (e.g., all coupling

terms).

� Detailed stress analysis

based on externally computed

extreme loads.


Multidisciplinary Design FrameworkEstimation of Extreme loads using HAWC2

� Fully resolved time simulations of all DLCs (+1000 simulations) is time

consuming, and inclusion of turbulence is not suited for gradient based

MDO,

� A reduced DLB has been developed, which requires <40 cases and

omits turbulence inflow.

Image from C Pavese, unpublished


Multidisciplinary Design FrameworkReduced Design Load Basis

Image from C Pavese, unpublished


Multidisciplinary Design FrameworkAerostructural Optimization Workflow Diagram

Optimizer Geometric properties Geometric properties Beam propsFrequencies

Fatigue DEL rateExtreme loads

Tower clearanceMaterial failure Objective function

Planform DVs Planform splines

Structural DVs Structural splines

Blade geometry Blade structureCross-sectional FE:

BECAS

WT control DVs Blade geometry Beam propsAeroelastic solver:

HAWCStab2

WT control DVs Blade geometry Beam propsAeroelastic solver:

HAWC2

Blade structure Extreme loadsCross-sectional FE:

BECAS

Mass properties AEP Extreme loads Cost function

Figure: Extended Design Structure Matrix diagram of the workflow of HawtOpt2.


10 MW Rotor Design StudyProblem Objective

minimizexp, xs, xoper

−AEP({xp, xs, xoper},p)

AEP({0, 0, 0},p)

subject to g(xp) ≤ 0,

hg(xs) ≤ 0,

hs(xs) ≤ 0,

k({xp, xs}) ≤ 0

(1)

where

� xp is the planform variables,

� xs is the structural variables,

� xoper is the wind turbine control variables,

� p is turbine parameters kept constant.


10 MW Rotor Design StudyProblem Design Variables

Parameter # of DVs Comment

Chord 6 -

Twist 5 Root twist fixed

Relative thickness 3 Root and tip relative thickness fixed

Blade prebend 4 -

Blade precone 1 -Blade length 1 -

Tip-speed ratio 1 -

Trailing edge uniax 2 Lower/Upper side

Trailing edge triax 2 Lower/Upper side

Trailing panel triax 2 Lower/Upper sideSpar cap uniax 4 Lower/Upper side

Leading panel triax 2 Lower/Upper side

Leading edge uniax 2 Lower/Upper side

Leading edge triax 2 Lower/Upper side

DP4, DP5, DP8, DP9 5 Lower/Upper spar cap position/width and web attachment

Total 60

Table: Design variables used in the optimization.


10 MW Rotor Design StudyProblem Constraints

Constraint Value Comment

max(chord) < 6.2 m Maximum chord limited for transport.

max(prebend) < 6.2 m Maximum prebend limited for transport.

max(rotor cone angle) > −5 deg -

min(relative thickness) > 0.24 Same airfoil series as used on the DTU 10MW RWT.

t/wsparcap > 0.08 Basic constraint to avoid spar cap buckling.

min(tip tower distance) > ref value Simplified DLC1.3 operational case with wsp=15 m/s pitch=0

deg.

Blade root flapwise moments (MxBR) < ref value Simplified DLC1.3 operational case with wsp=15 m/s pitch=0

deg.

Rotor thrust (FyTT) < ref value Simplified DLC1.3 operational case with wsp=15 m/s pitch=0deg.

Rotor torque < ref value Ensure that the rotational speed is high enough below rated to

not exceed generator maximum torque.

Blade mass < 1.01 * ref value Limit increase in blade mass to maintain equivalent production

costs.

Blade mass moment < 1.01 * ref value Limit increase in blade mass moment to minimise edgewise fa-tigue.

Lift coefficient @ r/R = [0.5 − 1.] < 1.35 Limit operational lift coefficient to avoid stall for turbulent inflow

conditions.

Ultimate strain criteria < 1.0 Aggregated material failure in each section for 12 load directions

for DLC1.3, DLC6.x.

Table: Non-linear constraints used in the design process.


10 MW Rotor Design StudyFinite Difference Gradient Quality

� The accuracy of the gradients is critical to get a rapidly and smoothly

converging optimization,

� Careful scaling of all design variables and correct choice of finite

difference step size,

� Two examples of fully coupled gradients exhibit fairly smooth

convergence,

� All parameters were scaled to match a step size of dx = 0.01,

corresponding to 1% of the representative scale of the parameters

0 1 2 3 4 5DV index

−0.07

−0.06

−0.05

−0.04

−0.03

−0.02

−0.01

0.00

0.01

d_ae

p_d_

chord

dx=1.0e-03dx=2.5e-03dx=5.0e-03dx=7.5e-03dx=1.0e-02dx=2.5e-02dx=5.0e-02dx=7.5e-02dx=1.0e-01

0.0 0.5 1.0 1.5 2.0 2.5 3.0DV index

−12

−10

−8

−6

−4

d_tip

pos_

d_r04u

niax

dx=1.0e-03dx=2.5e-03dx=5.0e-03dx=7.5e-03dx=1.0e-02dx=2.5e-02dx=5.0e-02dx=7.5e-02dx=1.0e-01


ResultsOptimized Blade Planform

0 20 40 60 80 100Blade running length [m]

0

1

2

3

4

5

6

7

Cho

rd le

ngth [m

]

BaselineNew design


−15

−10

−5

0

5

10

Blade

twist [de

g.]

BaselineNew design


20

30

40

50

60

70

80

90

100

Relative thickn

ess [%

]

BaselineNew design

0 20 40 60 80 100Blade radial coordiante [m]

7

6

5

4

3

2

1

0

1

Blade out of plane coordinate [-] Baseline

New design

Figure: Optimized blade planform compared to the baseline DTU 10MW RWT.


ResultsOptimized Blade Internal Structure

0.0 0.2 0.4 0.6 0.8 1.00

20

40

60

80

100

Thickn

ess [m

m]

Trailing edge paneltriaxuniaxbalsauniaxtriax

0.0 0.2 0.4 0.6 0.8 1.00

10

20

30

40

50

60

70

80

Thickn

ess [m

m]

Trailing paneltriaxuniaxbalsauniaxtriax

0.0 0.2 0.4 0.6 0.8 1.00

10

20

30

40

50

60

70

80

Thickn

ess [m

m]

Spar cap

triaxuniaxuniaxtriax

0.0 0.2 0.4 0.6 0.8 1.00

5

10

15

20

25

30

35

40

45

Thickn

ess [m

m]

Leading paneltriaxuniaxbalsauniaxtriax

0.0 0.2 0.4 0.6 0.8 1.00

10

20

30

40

50Th

ickn

ess [m

m]

Leading edge paneltriaxuniaxbalsauniaxtriax

Figure: Material stacking sequence for each region along the optimized blade.


ResultsOptimized Lofted Blade

� Internal structure optimized with very few geometric constraints,

� Main laminates placed forward in the cross-section and angled,


ResultsOptimized Load Distributions

0 20 40 60 80 100Blade radial coordinate [m]

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0Lo

cal t

hrus

t coe

ffici

ent [

-]

wsp=7.00wsp=8.00wsp=9.00wsp=10.00wsp=11.00


0

1000

2000

3000

4000

5000

6000

7000

8000

9000

Normal force [N/m]



−6

−5

−4

−3

−2

−1

0

1

Blade

torsion [deg

]



0

5

10

15

20

Angle of attack [deg]


Figure: Blade local thrust coefficients and normal forces (upper), and blade torsion andangle of attach (lower) for a range of wind speeds.


ResultsA closer look at the structural tailoring

� Initial design had very little torsional coupling,

� Bend twist coupling occurs ”hands off” due to the use of a fully coupled

MDO approach,

� The bend-twist coupling was achieved through a forward movement of

the shear center and reduction of torsional stiffness,

� The resulting coupling is referred to as ”shear twist coupling”,

� This coupling does not suffer from loss in flapwise stiffness, making it

more attractive that e.g. material coupling.


ResultsPower Curve

� Steady state AEP increased by 11.1%,

� Turbulent power curve evaluated at TI=10%, six seeds, AEP gain of

8.7%,

� Aeroelastically tailored blade loses power in turbulent conditions.

0 5 10 15 20 25Wind speed [m/s]

0

2000

4000

6000

8000

10000

12000

Mecha

nical P

ower [kW]

BaselineNew design

4 6 8 10 12 14Wind speed [m/s]

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

Pmek_t/Pmek_s [-]

BaselineNew design

Figure: Power curve for the optimized blade compared to the baseline design forsteady state conditions (dotted lines) and turbulent power curve with 10% reference TI(left), and the ratio between the turbulent and steady state power curves (right).


ResultsUltimate loads

0.20.4

0.60.8

1.01.2

1.4

AEP

Tower Clearance

Blade Root Flap

Blade Root Edge

Blade Root Tors.

Tower Bottom FA

Tower Bottom S2S

Tower Top FA

Tower Top S2S

AEP

Tower Clearance

Blade Root Flap

Blade Root Edge

Blade Root Tors.

Tower Bottom FA

Tower Bottom S2S

Tower Top FA

Tower Top S2S

Baseline Optimized Design

0.20.4

0.60.8

1.01.2

Blade Root Flap

Blade Root Edge

Blade Root Tors.

Tower Bottom FA

Tower Bottom S2S

Tower Top FA

Tower Top S2S

Blade Root Flap

Blade Root Edge

Blade Root Tors.

Tower Bottom FA

Tower Bottom S2S

Tower Top FA

Tower Top S2S

Baseline Optimized Design

Figure: Turbine extreme (left) and lifetime equivalent (right) loads relative to thebaseline DTU 10MW RWT computed using the full design load basis comprising of1800 cases.


ConclusionsSummary

� Fully coupled aerostructural design tool HAWTOpt2 used to design a 10

MW stretched blade,

� 8.7% increase in AEP compared to the DTU 10MW RWT, probably not a

representative increase compared to commercial blades (!),

� Final blade is the raw design coming out of the optimization, not modified

manually,

� Simultaneous tailoring of the internal structure and the aerodynamic

shape results in a bend-twist coupled blade,

� No previous knowledge of how to achieve the aeroelastic tailoring was

included in the optimization problem,

� Purely a result of an MDO approach!


ConclusionsFuture Work

� Design for manufacturability,

� More degrees of freedom:

Shear-twist coupling, material

coupling, sweep, all included in the

same optimization problem,

� Improvement of the extreme loads

predictions using multi-fidelity

optimization techniques (AMMF),

� Material based fatigue damage,

� Non-linear panel buckling in BECAS,

� More detailed and robust

cross-sectional meshing with

analytic gradients,

� Analytic gradients in BECAS.


Frederik Zahle - Design of an Aeroelastically Tailored 10 MW Wind Turbine Rotor

Technology

Transcript of Frederik Zahle - Design of an Aeroelastically Tailored 10 MW Wind Turbine Rotor