Zalkind 50 mw segmented ultralight rotor

1. 50 MW Segmented Ultralight Morphing Rotor
(SUMR): Design Concept and Controls Strategies
Dana Martin and Daniel Zalkind

2. Advanced Research Projects Agency-
Energy (ARPA-E)
• Fund high-potential, high-
impact energy technologies
that are too early for private-
sector investment
2
FloDesign’s Shrouded Wind Turbine
Accio Energy’s Electrohydrodynamic (EHD) wind
energy Generation System Makani Power’s Airborne Wind Turbine
Reduce
Emissions
Improve
Energy
Efficiency
Reduce
Energy
Imports
9/19/16 2016 Sandia Blade Workshop

3. Extreme Scale Turbines
9/19/16 2016 Sandia Blade Workshop 3
Larger turbines mean more energy captured and
reduces “plant” &“utility-integration” costs
Figure courtesy of Eric Loth

4. Segmented Ultralight Morphing
Rotors (SUMR)
4
• Aligns blade along axial loads
• Reduces rotor mass & facilitates
segmentation
• Enables lightweight, extreme scale
turbines, e.g. 13-50 MW
Downwind
Morphingwind
Metric Conv-13 SUMR-13 SUMR-50
Rotor Radius 102.5 m 107.5 m 200 m
Rated power 13.2 MW 13.2 MW 50 MW
Rotor mass 148.5Mg 72.3 Mg TBD
Levelized Cost of
Energy Savings 0% 33% 50%
𝝍
*Source: Steele et. al., Aerodynamics of an Ultralight Load-Aligned Rotor for Extreme-
Scale Wind Turbines
9/19/16 2016 Sandia Blade Workshop

5. Project Timeline
5
• Initial
design
• Goal: 25%
rotor
mass
reduction
CONR-13
• Optimize
based on
experience
from
SUMR-13i
• Goal: 25%
LCOE
reduction
SUMR-13i
Apply
lessons from
previous
rotors to
design of 50
MW rotor
SUMR-50
Design,
fabricate,
configure
and execute
a NREL field
test
SUMR-D
CONR: conventional rotor
LCOE: levelized cost of energy
SUMR: segmented, ultra-light, morphing rotor
April 2016 April 2017 April 2018 April 2019
• System design
• Aerodynamic design
• Structural design
• Control design
9/19/16 2016 Sandia Blade Workshop

6. System Design
• Outputs
– Morphing schedule
– Turbine configuration
6
System Design
[UVA]
Aerodynamic
Design
[UIUC]
Structural
Design
[Sandia]
Control System
Design
[CSM & UCB]
Hinged actuation
(active)
Aero-elastic deformation
(passive)
[Eric Loth, Carlos Noyes, Chris Qin, University of Virginia]
• Morphing concept
– Design hinge mechanism
– Test hinge mechanism
(water tunnel)
9/19/16 2016 Sandia Blade Workshop
cvcvc
c
Nacelle C.M. Overhang
Pre-cone
Tower Ht.
Wind Speed / Rated
Coning Angle (deg.)
Initial Coning Schedule for SUMR-13i

7. Aerodynamic Design
System Design
[UVA]
Aerodynamic
Design
[UIUC]
Structural
Design
[Sandia]
Control System
Design
[CSM & UCB]
F1-4846-1226
F1-3856-0738
F1-2655-0262
F1-2040-0087
F1-1822-0041
[Gavin Ananda, Suraj Bansal, Michael Selig, University of Illinois Urbana-Champaign]
• Coning rotor design code &
validation
• Aerodynamic design
– PROFOIL
Airfoil, rotor info.
9/19/16 2016 Sandia Blade Workshop 7

8. Structural Design
8
System Design
[UVA]
Aerodynamic
Design
[UIUC]
Structural
Design
[Sandia]
Control System
Design
[CSM & UCB]
(1) Maximum
Strain
(2) Tip
Deflection
(3) Fatigue
(4) Buckling
(5) Dynamics
and Flutter
üWill not break
Will not strike
tower
üGreater than 20 yrs
üStable structure
üNo turbine vibrations
üAero-elastic stability
[D. Todd Griffith, Chris Kelley, Sandia National Laboratories]
Blade structural
parameters
9/19/16 2016 Sandia Blade Workshop

9. Control System Design
• Control architecture
– Gains, set-points
• Time-series simulation
analysis using FASTv8
– Loads
– Deflections
– Power production
9
System Design
[UVA]
Aerodynamic
Design
[UIUC]
Structural
Design
[Sandia]
Control System
Design
[CSM & UCB]
[Kathryn Johnson, Dana Martin, Lucy Pao, Daniel Zalkind, CSM, UCB]
Control system,
validation of
turbine
configuration
9/19/16 2016 Sandia Blade Workshop

10. Field Testing & Cost Analysis
10
System Design
[UVA]
Aerodynamic
Design
[UIUC]
Structural
Design
[Sandia]
Control System
Design
[CSM & UCB]
Source: NREL Image Gallery
LCOE =
CapEx ∗ Finance + OpEx
AEPnet
[Rick Damiani, Lee Jay Fingersh, Patrick Moriarty, Tyler Stehly, NREL]
9/19/16 2016 Sandia Blade Workshop

11. Minimum Control Requirements
• Given a rotor design, our goal
is to design real-time
controllers that:
– “based on the information
about the condition of the wind
turbine and/or its environment,
– adjust the turbine in order to
maintain it within its operating
limits.”*
11
*Source: IEC 61400-1
9/19/16 2016 Sandia Blade Workshop
Note: turbines are not
typically controlled from
the nacelle

12. Performance Metrics
• These operating limits are defined
by the wind turbine designer,
which include
– Generator overspeed, overload or
fault
– Ultimate blade loads and blade-to-
tower clearance in extreme or
extrapolated events, and
– Design lifetime due to fatigue
loading.
12
Gen. speed
threshold
Maximum gen.
speed
Rated gen.
speed
Gen. Speed (rpm)
Time (s)Blade Root Bend. Moment (kNm)
9/19/16 2016 Sandia Blade Workshop

13. Control Overview – Operating
Regions
9/19/16 2016 Sandia Blade Workshop 13
0 5 10 15 20 25
0
0.5
1
1.5
2
2.5
3
Wind Speed (m/s)
Power(MW)
Example Power Curves for 2.5 MW Wind Turbine
Region 1
• Region 1: Low wind speed
– Wind turbines not run, because power
available in wind is low compared to losses
in turbine system
• Region 2: Medium wind speeds
– Variable-speed turbines vary speed to
maximize aerodynamic efficiency
• Region 3: High wind speeds
– Variable-pitch turbines limit power to avoid
exceeding safe electrical and mechanical
load limits
Wind
Power
Available
Max Power Coeff » 0.50
Region 2
Region 3
Expected
Turbine
Power
(Slide courtesy of Prof. Lucy Pao)

14. Baseline Control
• Jonkman et al., “Definition of a
5-MW Ref. Wind Turbine for
Offshore System
Development,” 2005.
Baseline Controller
Parameters of
NREL 5-MW
Parameter Value
Blade Length 63 m
Rotor Inertia 3.87x107 kg-m2
Rated Torque 47 kNm
Rated Rotor
Speed
12.1 rpm
Configuration Upwind, 3-bladed,
2.5° coning
Cp Surface
5-MW Ref. Params.SNL 100-03 Params.
Parameters of
SNL 100-03
Parameter Value
Blade Length 102.5 m
Rotor Inertia 2.66x108 kg-m2
Rated Torque 115 kNm
Rated Rotor
Speed
7.43 rpm
Configuration Upwind, 3-bladed,
2.5° coning
Cp Surface
Parameter Value
Blade Length 102.5 m
Rotor Inertia 1.77x108 kg-m2
Rated Torque 115 kNm
Rated Rotor
Speed
7.43 rpm
Configuration Downwind, 2-
bladed, var. coning
Cp Surface
SNL 100-03 (D2) Params.
Parameters of
SNL 100-03 (D2)
Parameter Value
Blade Length ~100 m
Rotor Inertia ??
Rated Torque ~115 kNm
Rated Rotor
Speed
~7 rpm
Configuration ??
Cp Surface
SUMR-13i Params.
??
Parameters of
SUMR-13i
NREL
5-MW
SNL 100
13.2 MW
SNL 100
(D2)
SNL 100
(coning)
SUMR-
13i
SUMR-13SUMR-DSUMR-50
9/19/16 2016 Sandia Blade Workshop 14

15. • Transfer function describes
input/output dynamics in the
frequency domain
• In this case, the poles
represent a time constant for
the response of the system to
the controlled input (i.e.
generator torque).
• Linearized system at several
coning angle, wind speed
pairs
• Pole-Zero Map
• Effects:
• Dynamics change with coning
angle
• Different gains need to be
calculated for same power &
speed regulation
𝐺 𝑠 =
𝑌(𝑠)
𝑈(𝑠)
Incorporating Coning – Dynamics
159/19/16 2016 Sandia Blade Workshop
Real Axis (seconds-1)
Pole-Zero Map
Imaginary Axis (seconds-1)

16. Incorporating Coning – Steady
Precone
• Implemented steady-state pre-
cone schedule (right)
• Ran turbulent simulations
using FASTv8
16
*Source: University of Virginia
Wind Speed / Rated
Coning Angle (deg.)
Turbine Characteristics
Number of Blades Airfoil Rated Torque (kN-m) Rated Power (MW) Rotor Direction
2 SNL100-03 FB 115 13.2 Down Wind
12.5°
9/19/16 2016 Sandia Blade Workshop

17. 9/19/16 2016 Sandia Blade Workshop
Incorporating Coning – Rotor
Torque
17
Turbine Characteristics
Number of Blades Airfoil Rated Torque (kN-m) Rated Power (MW) Rotor Direction
2 SNL100-03 FB 115 13.2 Down Wind
Average Rotor Torque (kN-m)
Average Rotor Torque vs. Wind Speed
Wind Velocity (m/s)
Aero Torque vs. Coning Angle
Coning Angle (degrees)
Aero Torque @ 10m/s wind (kN-m)

18. 2016 Sandia Blade Workshop9/19/16
Maximum and Minimum Tip Displacements
Tip Displacement (m)
Incorporating Coning – Extreme
Loads
18
Turbine Characteristics
Number of
Blades
Airfoil Rated Torque
(kN-m)
Rated Power
(MW)
Rotor Direction Design Load Case Tested
2 SNL100-03 FB 115 13.2 Down Wind Extreme Turbulence Model
(ETM)
Constant vs. Scheduled Max. Displacements
% Change in Out of Plane Disp.
Root Moment Bending Loads
Root Moments (kN-m)
Constant vs. Scheduled Max. Loads
% Change in OOP Bld. Root Mom.

19. Incorporating Coning-Average Loads
199/19/16 2016 Sandia Blade Workshop
Turbine Characteristics
Number of Blades Airfoil Rated Torque (kN-m) Rated Power (MW) Rotor Direction
2 SNL100-03 FB 115 13.2 Down Wind
Avg. Out of Plane Blade Root Mom. (kN-m)
Wind Velocity (m/s) Wind Velocity (m/s)
Avg. In Plane Blade Root Mom. (kN-m)

20. Advanced Control Methods for
Reducing Loads
• Power & speed
regulation
• Oscillations
• Blade loads
• Incoming wind
measurement
20
Baseline Controller
Rotor Params.
DT & Tower
Damper
Indiv. Pitch
Control
Feedforward
Control
Actuators
Lidar
9/19/16 2016 Sandia Blade Workshop

21. Control Challenge: Modelling
21
Hub
Drivetrain
Blades
Hinges
• Rotor layout
• Degrees of freedom,
states
• Control inputs
• Disturbances
Rotor speed
Tip deflection
Gen. torqueWind Blade pitch
Flap angle
9/19/16 2016 Sandia Blade Workshop

22. Control Challenges: Wind
Resource
• Shear
– Uneven rotor loading
– Shear effects should increase with
rotor diameter
• Turbulence
– Turbulent length scale ~ blade
length
• Normally assumed to be much larger
• Introduces uncorrelated loading along
blade
22
𝝎
Loads
Deflections
9/19/16 2016 Sandia Blade Workshop

23. Control Opportunity: Equations of
Motion
• 𝑥̇ = 𝑓 𝑥, 𝑢, 𝑑
→ 𝑥̇ = 𝐴𝑥 + 𝐵𝑢 + 𝐸𝑑
• 𝑦 = ℎ 𝑥, 𝑢, 𝑑
→ 𝑦 = 𝐶𝑥 + 𝐷𝑢 + 𝐹𝑑
• Stability
• Controllability
– Can you change the state using the
inputs (and which ones)?
• Observability
– Can you determine the state by
viewing the output (and which ones)?
23
Blades:
𝑀K 𝑥̈K + 𝐷K 𝑥̇K + 𝐾K 𝑥K = 𝑓N (𝜃, 𝜆)
Tower (not shown):
𝑀N 𝑥̈N + 𝐷N 𝑥̇N + 𝐾N 𝑥N = 𝑓N 𝜃, 𝜆
Drivetrain & Control:
𝜔 =
R
S
𝜏U − 𝜏W
𝜃 = 𝐾X 𝜔 − 𝜔Y + 𝐾Z∫ 𝜔 − 𝜔Y 𝑑𝑡
𝑥K
𝜔
𝜃
𝜃
9/19/16 2016 Sandia Blade Workshop
𝑥N

24. Control Challenges: Structures
• Loads
– Mass reduction → increased deflection
– Coning & size increase → increase in-plane loads
• Actuators
– What are the demands (e.g. time delays) and
can they be met with current tech.?
• Larger blades require more powerful pitch actuators
• Implementation of a pitch/coning actuator system
249/19/16 2016 Sandia Blade Workshop

25. Control Opportunity: Smart Rotor
Control
• Control surfaces
– Partial pitch, flaps, microtabs, vortex
generators, etc.
• Actuators
– Faster bandwidths to dampen aerodynamic
disturbances & structural vibrations
• Sensors
– For inflow velocities, pressures,
accelerations, deflections and strains
• Control
– Centralized → Distributed
259/19/16 2016 Sandia Blade Workshop

26. Project Timeline
26
• Initial design
• Goal: 25%
rotor mass
reduction
CONR-13
• Optimize
design based
on experience
from SUMR-13i
• Goal: 25%
LCOE reduction
SUMR-13i
Apply lessons
from previous
rotors to design
of 50 MW rotor
SUMR-50
Design, fabricate,
configure and
execute a NREL
field test
SUMR-D
April 2016 April 2017 April 2018 April 2019
We are
here
9/19/16 2016 Sandia Blade Workshop

27. Thank You!
Questions or Comments?
279/19/16 2016 Sandia Blade Workshop
Contact:
Dana Martin / dmartin@mymail.mines.edu
Daniel Zalkind / daniel.zalkind@colorado.edu

28. Extra
289/19/16 2016 Sandia Blade Workshop

29. Advanced Control - LPV
Linear Parameter Varying (LPV) Control is a control method which utilizes
Linearized State Space Matrices around several Operating Points contained
within the plant operation envelope in order to schedule control gains.
29
Operating Points
𝑥̇ = 𝑨(𝑣_)𝑥 + 𝑩(𝑣_)𝑢
y= 𝑪(𝑣_)𝑥 + 𝑫(𝑣_)𝑢
9/19/16 2016 Sandia Blade Workshop

30. Performance Metric Summary
• These operating limits are defined by the wind turbine designer…
30
*Source: IEC 61400-1
Turbine
Parameters
Electrical Mechanical
• Generator Power
§ RMS Power
§ Frequency above
rated
§ Maximum
Threshold
• Turbine Component Loads
§ Ultimate Loads
§ Fatigue Loads
• Turbine Component Displacements
§ Tower fore-aft
§ Tower side-side
§ Blade in plane and out-of-plane
9/19/16 2016 Sandia Blade Workshop

31. Performance Metric Summary
• Given a rotor design, our goal
is to design real-time
controllers that, “based on
the information about the
condition of the wind turbine
and/or its environment,
adjust the turbine in order to
maintain it within its
operating limits.”*
31*Source: IEC 61400-1
Controller
Environment
+
Turbine
Parameters
Coning Angle
Pitch Angles
Generator
Torque
Sensor Measurements
(i.e. blade loads, blade
displacements, Rotor Speed)
Wind Turbine
9/19/16 2016 Sandia Blade Workshop

32. Control Opportunities
• Different model/control synthesis techniques
– Here we might talk about SS models for wind turbines & how they
are changed when size increases and weight is reduced
– Also, controller synthesis: LPV, MPC
– Still learning what challenges exist
329/19/16 2016 Sandia Blade Workshop

33. Incorporating Coning -
Mechanism
33*Source: University of Virginia
Aero-elastic Deformation (passive) Hinged Actuation(Active)
vs
9/19/16 2016 Sandia Blade Workshop

34. Incorporating Coning - Method
• A pivotal topic of research
is how to implement the
coning.
– Aero-elastic deflection or
– Active coning actuated by
an active hinge
• Single point of coning
• Multiple points along blade
34
*Source: “A morphing downwind-aligned rotor concept based on a 13-MW wind turbine”
9/19/16 2016 Sandia Blade Workshop

35. Incorporating Coning - Schedule
• The coning schedule is
designed to decrease
average root blade
bending moments and
protect turbine blades
during hurricane force
winds
35
*Source: “A morphing downwind-aligned rotor concept based on a 13-MW wind turbine”
9/19/16 2016 Sandia Blade Workshop

36. 0 5 10 15 20 25
0
0.5
1
1.5
2
2.5
3
Wind Speed (m/s)
Power(MW)
Example Power Curves for 2.5 MW Wind Turbine
Region 1
Operating Regions
• Region 1: Low wind speed (below
6 m/s = 21.6 km/h)
– Wind turbines not run, because
power available in wind is low
compared to losses in turbine
system
• Region 2: Medium wind speeds
(6 m/s to 11.7 m/s)
– Variable-speed turbines vary speed
to maximize aerodynamic efficiency
v Region 3: High wind speeds (above
11.7 m/s = 42.1 km/h)
§ Variable-pitch turbines vary the pitch
of blades to limit power to avoid
exceeding safe electrical and
mechanical load limits
Wind
Power
Available
Max Power Coeff » 0.50
Region 2
Region 3
Lucy Pao August 2016
Expected
Turbine
Power
9/19/16 2016 Sandia Blade Workshop 36

37. 0 5 10 15 20 25
0
0.5
1
1.5
2
2.5
3
Wind Speed (m/s)
Power(MW)
Example Power Curves for 2.5 MW Wind Turbine
Region 1
Operating Regions
• Region 1: Low wind speed (below
6 m/s)
– Wind turbines not run, because
power available in wind is low
compared to losses in turbine
system
• Region 2: Medium wind speeds
(6 m/s to 11.7 m/s)
– Variable-speed turbines vary speed
to maximize aerodynamic efficiency
v Region 3: High wind speeds (above
11.7 m/s)
§ Variable-pitch turbines vary the pitch
of blades to limit power to avoid
exceeding safe electrical and
mechanical load limits
Wind
Power
Available
Region 3
De-rated
Turbine
Power
Lucy Pao August 2016
Max Power Coeff » 0.50
Region 2
Expected
Turbine
Power
9/19/16 2016 Sandia Blade Workshop 37

38. 50 MW Segmented Ultralight Morphing Rotors (SUMR)
for Wind Energy
2016 – 2019
[ E. Loth, D. T. Griffith, K. Johnson, P. Moriarty, L. Pao, M. Selig ]
Lucy Pao August 2016
wind
9/19/16 2016 Sandia Blade Workshop