Evan Gaertner University of Massachusetts, Amherst IGERT Seminar Series October 1st, 2015 Floating...
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Transcript of Evan Gaertner University of Massachusetts, Amherst IGERT Seminar Series October 1st, 2015 Floating...
Evan GaertnerUniversity of Massachusetts, Amherst
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
9
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
15
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
16
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
17
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
18
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 [email protected]
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
21
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
22
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