Today, Wind Turbine OEMS utilize design load cases for the design and certification of wind turbines. These load cases are applied to ensure that turbines operate in a stochastic environment for at least 20 years. However, reliability analysis should not stop at the design stage. Once a turbine is commissioned, consequent reliability analysis should also be conducted in order to understand how long a turbine will truly last at an installed location with the exposed environmental conditions. View the Webinar Recording at: http://sentientscience.com/resource-library/videos/webinar-recordings/wind-load-analysis-drivetrain-reliability/

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Wind Load Analysis
for Drivetrain Reliability

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Host
Natalie Hils
Director, of Revenue Marketing
nhils@sentientscience.com
+1 716.807.8655
Wind Load Analysis for Drivetrain Reliability

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Webinar Instructions
Wind Load Analysis for Drivetrain Reliability

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DigitalClone® Material Science Differentiation
☑ Extend Life☑ Root Causes☑ Long-Term Forecast
Wind Load Analysis for Drivetrain Reliability

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Sentient Science Customers
Wind Load Analysis for Drivetrain Reliability

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Outline
• Background and motivation for wind turbine system modeling
• Details on Sentient’s wind turbine system modeling approach
• Blade and tower reverse engineering
• Controller configuration and tuning
• Turbine-level modeling
• Translation of turbine model to prediction of turbine component
loads and life
• Validation of turbine modeling
• Summary
Wind Load Analysis for Drivetrain Reliability

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Wind Loads Challenge
Need to understand the impact loading events have on each unique asset to
predict when subcomponents are going to fail
Currently in Industry:
1. Wind Loads are captured on a wind farm level basis, not turbine by turbine
basis
2. Used in design stage, not during operation
3. Majority of SCADA is under-utilized due to large amount of data produced
Wind Load Analysis for Drivetrain Reliability

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Models Applications
Wind Load Analysis for Drivetrain Reliability
Component
Type
Uprate/
Derate
Supply Chain
Forecasting
Operation &
Maintenance
Planning
Turbine
Analysis for
Repowering
Asset Life
Prediction

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Presenter
Dr. Adrijan Ribaric
Vice President, Systems Technology
aribaric@sentientscience.com
Wind Load Analysis for Drivetrain Reliability

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Wind Turbine System Dynamics
• Usually used at Design Stage
• Important to understand loads and
reliability of all components
• Important to material-based as
well
Wind Load Analysis for Drivetrain Reliability

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Poll Question
Wind Load Analysis for Drivetrain Reliability

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Overview of Sentient’s Turbine Modeling Approach
Wind Load Analysis for Drivetrain Reliability
1.Wind Speed
2.Wind Shear
3.Turb. Intensity
4.Air Density
5.Wind Direct. HT
6.Wind Direct. VT
1.Rotor Speed
2.Gen. Power
3.Blade Pitch
Wind Data
1.Fx (Thrust)
2.Fy
3.Fz (Weight)
4.Mx (Torque)
5.My (Yaw Moment)
6.Mz (Pitch Moment)
1.Rotor Speed
2.Gen. Power
3.Blade Pitch
Turbine Loads
input output
1.Blade Moments
2.Blade Deflections
Compare, measured vs simulated
• Turbine model simulates the interaction between
inertial, elastic, and aerodynamic forces
• Turbine model is based on the aeroelastic software
package FAST (NREL)

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Inputs to Turbine System Model: Blades
Wind Load Analysis for Drivetrain Reliability
• Information on blade weight, length, and
twist is determined from turbine
specifications
• The blade is then re-engineered to match the
efficiency and power curves as calculated
from the turbine SCADA history
• After achieving a close blade match, the
parameters of the re-engineered blade are
implemented in the turbine model

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Inputs to Turbine System Model: Rotor Blades
Wind Load Analysis for Drivetrain Reliability
• Blade polars – lift and drag coefficients as a function of angle
of attack and Reynolds number
• Mass and stiffness distribution along the length of the blade

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Inputs to Turbine System Model: Rotor Blades
Wind Load Analysis for Drivetrain Reliability
• Blade polars – lift and drag coefficients as a function of angle
of attack and Reynolds number
• Mass and stiffness distribution along the length of the blade

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Inputs to Turbine System Model: Turbine Controller Settings
Wind Load Analysis for Drivetrain Reliability
Control
Law
Turbine
β*
τg
ωdesired ωmeasured
Control
Law
Turbine
β
τg,rated
ωdesired ωmeasured
Generator Torque Controller
Blade Pitch Controller
Annoni, 2016

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Inputs to Turbine System Model: Turbine Controller Settings
Wind Load Analysis for Drivetrain Reliability
0
200
400
600
800
1000
1200
1400
1600
0 5 10 15 20 25
MeanPower(kW)
Wind Speed (m/s)
Published Power Curve
Power Curve from SCADA
Power Curve from Turbine Modeling

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Inputs to Turbine System Model: Tower Bending Properties
Wind Load Analysis for Drivetrain Reliability
0
10
20
30
40
50
60
70
80
0 100 200 300
TowerHeight[m]
Stiffness [GPa]
Bending
Torsion

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Poll Question
Wind Load Analysis for Drivetrain Reliability

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Turbine System Model - Workflow
Time series of
hub loads:
1. Fx (Thrust)
2. Fy (lateral)
3. Fz (weight)
4. Mx (Torque)
5. My (Pitch)
6. Mz (Yaw)
Turbine Specific
(dynamic, 10 min stat.)
1. Wind Speed
2. Wind Direction
3. Yaw position
4. Operation State
AEROELASTIC MODEL
Wind turbine
(10 min simulation)
Controller
Site Specific (static)
1. Roughness Length
2. Upflow angle
3. Wind Shear
Exponent (annual)
4. Airdensity (annual)
Wind Pre-Processing
(dynamic, 10 min stat.)
1. Wind Speed
2. Turbulence Intensity
3. Wind shear
4. Air density
5. Inflow horizontal
6. Inflow vertical
Wind Load Analysis for Drivetrain Reliability
Met-Tower
(dynamic, 10 min stat.)
1. Wind Shear
Exponent
2. Airdensity
3. Wind Direction
4. Turbulence Intensity
Wind MODEL
Full-field flow
(10 min simulation)
(source: Erich Hau, “Windkraftanlagen”, Springer Verlag, 1988)

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Translation of Turbine Model Outputs into Applied Loads on Drivetrain
• Fx = thrust load
• Fy = horizontal load
• Fz = vertical load (weight)
• Mx = Torque
• My = overturning moment
(induced by weight and wind
shear)
• Mz = yaw moment
(e.g., induced by turbulence)
Loads (Fx, Fy, Fz, Mx, My, Mz) from rotor blades
Main bearing
Main shaft
Gearbox
Wind Load Analysis for Drivetrain Reliability

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Turbine Component Analysis - Bearing Analysis Tool (BAT)
Wind Load Analysis for Drivetrain Reliability
sliding velocity
distribution
load distribution
dynamic motion data history of all internal components
orientation, angular velocity and acceleration, torque
position, velocity and acceleration, force
component interaction data
steady or transient operation

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Turbine Component Analysis – Gear Application Program (GAP)
Variable Pinion Wheel
Number of Teeth 16 70
Normal module (mm) 14
Normal Pressure Angle (deg.) 20
Normal Helix Angle (deg.) 11
Outside Diameter (mm) 278.75 1067.05
Root Diameter (mm) 201.65 996.93
Profile shift 0.7815 1.394
Fillet Radius (mm) 3.5 5.6
Face Width (mm) 275 265
Tip Relief Length (mm) 22.44 22.44
Tip Relief Magnitude (mm) 0.076 0.076
Root Relief Length (mm) 0 0
Root Relief Magnitude (mm) 0 0
Flank End Relief Length (mm) 27.5 13.25
Flank End Relief Magnitude (mm) 0.009 0.015
Crowning Magnitude (mm) 0.034 0.014
Young’s Modulus (Mpa) 206000 206000
Poisson Ratio 0.3 0.3
Center Distance (mm) 640
Gears Axial Offset (mm) 0
Misalignment (mrad) 0.053
Speed (rpm) 380.00 -
Torque (N.m) 55249 -
Wind Load Analysis for Drivetrain Reliability

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Validation of Turbine Load Model
For a select set of turbines, loads on the main shaft were
physically measured and compared to the simulation
The captured loads are:
o 𝜔 = Speed
o Mx = torque
o My = overturning moment (e.g., induced by weight and wind
shear)
o Mz = vertical moment (e.g., induced by turbulence)
Wind Load Analysis for Drivetrain Reliability
1.5MW turbine

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Validation of Turbine Load Model
• Two strain gauges to measure
bending moment (separated by 90o)
• One strain gauge to measure torque
moment
• One accelerometer to capture hub
speed
Wind Load Analysis for Drivetrain Reliability
Sensor
RS GS

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Validation of Turbine Load Model
Wind Load Analysis for Drivetrain Reliability
0
100
200
300
400
500
600
700
800
900
1000
0 100 200 300 400 500 600
RotorTorque[kNm]
Time [s]
SCADA Sensor Turbine Model

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Validation of Turbine Load Model
Wind Load Analysis for Drivetrain Reliability
0
5
10
15
20
25
0 20 40 60 80 100 120
HubSpeed[RPM]
Time [s]
SCADA Sensor Turbine Model

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Validation of Nacelle Wind Measurement as Modeling Input
Wind Load Analysis for Drivetrain Reliability
TurbineMeteorological
Tower
0
2
4
6
8
10
12
0 5 10 15 20 25 30
Frequency[%]
Wind Speed [m/s]
Met-Tower (45m)
Nacelle (80m)

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Validation of Nacelle Wind Measurement as Modeling Input
Wind Load Analysis for Drivetrain Reliability
TurbineMeteorological
Tower
0
10
20
30
40
50
60
70
0 5 10 15 20 25 30
TurbulenceIntensity[%]
Wind Speed [%]
Met-Tower (45m)
Nacelle (80m)

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Validation of Nacelle Wind Measurement as Modeling Input
Wind Load Analysis for Drivetrain Reliability
TurbineMeteorological
Tower

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Poll Question
Wind Load Analysis for Drivetrain Reliability

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Turbine Load History
• To understand what loads a
turbine experienced over its
lifetime, we need to simulate its
complete history
• The history can contain of several
years
• Simulating its complete history
with a full dynamic model is
almost impossible
• For that reason, we convert our
Turbine Model into a Reduced
Order Model (ROM)
Wind Load Analysis for Drivetrain Reliability

33. © 2016 Sentient Science Corporation – Confidential & Proprietary
Turbine System Modeling of Dynamic Events
Wind Load Analysis for Drivetrain Reliability
0
5
10
15
20
0 10 20 30 40
RotorSpeed[rpm]
Time [s]
(source: https://youtu.be/dvrttCzpUh4)

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Turbine System Modeling of Dynamic Events
Wind Load Analysis for Drivetrain Reliability

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Summary
• Accurate life prediction of wind turbine components requires detailed turbine-
level modeling
• Sentient performs aeroelastic modeling of wind turbines to extract loads on
critical components
• Sentient’s approach utilizes reverse engineering to determine the properties of
the full turbine, including the blades and the controller
• Turbine model is wrapped within a reduced order modeling framework to provide
scalable, fast, individualized predictions of turbine component loads and life
• SCADA-based wind conditions are used as an input to the reduced order model,
having been validated for accuracy using uptower sensor and meteorological
tower measurements
Wind Load Analysis for Drivetrain Reliability

36. © 2016 Sentient Science Corporation – Confidential & Proprietary
Models Applications
Wind Load Analysis for Drivetrain Reliability
Component
Type
Uprate/
Derate
Supply Chain
Forecasting
Operation &
Maintenance
Planning
Turbine
Analysis for
Repowering
Asset Life
Prediction

37. © 2016 Sentient Science Corporation – Confidential & Proprietary
Thank you
Meet the Team!
Upcoming White Paper:
1. Seasonal effect of the load distribution of a wind turbine – May 2017
2. True fatigue load analysis based on SCADA – May 2017
Upcoming Webinars:
1. Moventas GE 1. Extra Life Gearbox Achieves 4x Life - May 9th 8AM EST & 1PM EST
Wind Load Analysis for Drivetrain Reliability

38. © 2016 Sentient Science Corporation – Confidential & Proprietary
Questions?
Natalie Hils
Director, Revenue Marketing
nhils@sentientscience.com
+1 716.807.8655
Dr. Adrijan Ribaric
Vice President, Systems Technology
aribaric@sentientscience.com
Wind Load Analysis for Drivetrain Reliability