Evan GaertnerUniversity of Massachusetts, Amherst

egaertne@umass.edu

IGERT Seminar SeriesOctober 1st, 2015

Floating Offshore Wind Turbine Aerodynamics and Optimization

Opportunities

2

Agenda

Floating Wind Turbine Aerodynamics Dynamics Stall Design Optimization

3

Floating Offshore Wind TurbinesAdvantages:Access to deeper water

• More useable area• Further from onshore lines of site• Reduce impact to important near shore

habitatsSimplified installation

• Tow-out installation• Reduce environmental impacts from pile

driving

4

Platform Motion

Wind and wave loading Non-rigid mooring system

Complex platform motion • 6 transitional and rotational Degrees of Freedom

Adverse Affects:• Increased aerodynamic complexity• Stronger cyclical loading• Requires more sophisticated controls

5

Velocity from Platform MotionSkewed flowFrom pitch or yawBlade moves

• Toward wind: increased velocity• Away from wind: decreased velocity

Occurs at rotational frequency

Wake interactionFrom pitch or surgeRotor moves through its own wakeCan causes flow reversals and turbulenceOccurs at platform motion frequency

6

Wake Induced Dynamic Simulator (WInDS)

A free-vortex wake method• Developed to model rotor-scale

unsteady aerodynamics By superposition, local velocities

are calculated from different modes of forcing

Previously neglected blade section level, unsteady viscous effects

induced platformU U U U [2]

Blade Scale Unsteadiness

8

Quasi-Steady Aerodynamics Aerodynamic properties of

airfoils determined experimentally in wind tunnels

Lift increases linearly with angle of attack (α)

At a critical angle, flow separates and lift drops• “Stall”

WInDS used quasi-steady data

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Dynamic Stall

10

Dynamic Stall Flow MorphologyStage 1 Stage 2 Stage 2-3 Stage 3-4 Stage 5

[3]

Lift C

oef,

C L

Drag

Coe

f, C D

Mom

ent C

oef,

C M

Angle of Attack, α (°) Angle of Attack, α (°) Angle of Attack, α (°)

11

Modeling Dynamic Stall: Leishman-Beddoes (LB) Model Semi-empirical method

• Use simplified physical representations• Augmented with empirical data

Model Benefits• Commonly used, well documented• Minimal experimental coefficients• Computationally efficient

[3]

12

Example 2D LB validation: S809 Airfoil, k = 0.077, Re = 1.0×106

10 15 20 25 30

0.5

1

1.5

2

Coe

f. of

Lift

, Cl

Angle of Attack, [ ]

mean=20 , amplitude=10

10 15 20 25 30

0.5

1

1.5

2

Coe

f. of

Lift

, Cl

Angle of Attack, [ ]

mean=20 , amplitude=10

5 10 15 20 25

0.5

1

1.5

2

Coe

f. of

Lift

, Cl

Angle of Attack, [ ]

mean=14 , amplitude=10

5 10 15 20 25

0.5

1

1.5

2

Coe

f. of

Lift

, Cl

Angle of Attack, [ ]

mean=14 , amplitude=10

0 5 10 15 20

0

0.5

1

1.5

Coe

f. of

Lift

, Cl

Angle of Attack, [ ]

mean=8 , amplitude=10

0 5 10 15 20

0

0.5

1

1.5

Coe

f. of

Lift

, Cl

Angle of Attack, [ ]

mean=8 , amplitude=10

LB model validated against 2D pitch oscillation data

10 15 20 25 30

0.5

1

1.5

2

Coe

f. of

Lift

, Cl

Angle of Attack, [ ]

mean=20 , amplitude=10

10 15 20 25 30

0.5

1

1.5

2

Coe

f. of

Lift

, Cl

Angle of Attack, [ ]

mean=20 , amplitude=10

5 10 15 20 25

0.5

1

1.5

2

Coe

f. of

Lift

, Cl

Angle of Attack, [ ]

mean=14 , amplitude=10

5 10 15 20 25

0.5

1

1.5

2

Coe

f. of

Lift

, Cl

Angle of Attack, [ ]

mean=14 , amplitude=10

0 5 10 15 20

0

0.5

1

1.5

Coe

f. of

Lift

, Cl

Angle of Attack, [ ]

mean=8 , amplitude=10

0 5 10 15 20

0

0.5

1

1.5

Coe

f. of

Lift

, Cl

Angle of Attack, [ ]

mean=8 , amplitude=10

13

WInDS-FAST Integration WInDS was originally written as a standalone

model in Matlab• Decouples structural motion and the aerodynamics

Integrated into FAST v8 by modifying the aerodynamic model, AeroDyn • Fully captures the effects of aerodynamics and

hydrodynamics on platform motions changes the resulting aerodynamics

OC3/Hywind Spar Buoy

Design Optimization

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Rotor DesignDesign ProcessStart with known optimal blade shapeModify for practical structural and manufacturing concerns

ProblemUses ideal conditions for aerodynamic analysis: uniform, steady, non-skewed flow

Typical optimization projects in the literation:More sophisticated modelsMore design variables

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Research Goal Inform design process with realistic

probability distributions of steady and unsteady condition• Operating conditions are never ideal!

Include minimization of load variability as a design goal

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Integrated Design of Offshore Wind Turbines

Process: Sequential design of subsystems

Problem:Optimized subsystemsSub-optimal global system

Solution:Multi-objective, multi-disciplinary, iterative optimization

TurbineDesign

Platform Design Controls

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Interdisciplinary OpportunitiesAdditional design goals could include:Lower tip speed ratios

• Reduce risk of bird strikesLarger turbine rotors

• Allow smaller wind farms with fewer seafloor disturbancesOptimization for deeper waters farther from shore

• Reduce competition for use or view-shed concerns

Open to suggestions for other interdisciplinary objects!

Questions?

Evan Gaertneregaertne@umass.edu

This work was supported in part by the NSF-sponsored IGERT: Offshore Wind Energy Engineering, Environmental Science, and Policy

and by the Edwin V. Sisson Doctoral Fellowship

Thank You!

Supplemental Slides

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Span-wise Unsteadiness

0.2 0.4 0.6 0.8 10

0.05

0.1

0.15

Blade Span, r/R

Ave

rage

Red

uced

Fre

quen

cy, k

Spanwise kQuasi-steady line

AoA predominately varying cyclically with rotor rotation, driven by:• Mean platform pitch: ~4-5°• Rotor shaft tilt: 5°

0.2 0.4 0.6 0.8 10.05

0.1

0.15

Blade Span, r/R

CL S

tand

ard

Dev

iatio

n

LB ModelStatic Data

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Dynamic Stall

10 12 14 16 18

1.3

1.4

1.5

1.6

1.7

1.8

Angle of Attack, ( )

Lift

Coe

f., C

L

Span Location r/R = 0.186

LB ModelStatic Data

5 6 7 80.9

1

1.1

1.2

1.3

1.4

Angle of Attack, ( )

Lift

Coe

f., C

L

Span Location r/R = 0.381

LB ModelStatic Data