1. Dynamic analysis of wind turbines subjected to Ice loads
Sudhakar Gantasala
PhD student

2. How the dynamic behavior of wind turbine blades change due to ice ?
March 14, 2017
Luleå University of Technology
How the dynamic behavior of wind turbine blades change due to ice ?
Depends on operating conditions
Varies from turbine to turbine
Modifies aerofoil shapes of the blade
Ice shapes and mass
Increases mass density
Reduces lift and increases drag forces
Introduces asymmetry in the blade assembly
Structural and aerodynamic changes in the blade due to ice
Power reduces
Aerodynamic loads decrease
Structural loads increase
Natural frequencies reduce
Aeroelastic damping factors decrease
Influence of icing on power, loads and vibrations of the turbine

3. Ice shapes from references
March 14, 2017
Luleå University of Technology
Ice shapes from references f A
x=0
x=l
Parameters:
1. Span ( l)
2. Sine curve frequencies (f)
3. Exp.coefficient (k)
Different ice shapes are recreated using superposition of different sine curves.

4. Leading edge ice modeling
March 14, 2017
Luleå University of Technology
Leading edge ice modeling #
# Beaugendre et al, “Development of a second generation in-flight icing simulation code”,
Journal of Fluids Engineering, 2006, 128(2), pp

5. Influence of icing on power
March 14, 2017
Luleå University of Technology
Influence of icing on power

6. CFD simulations of iced aerofoil
March 14, 2017
Luleå University of Technology
CFD simulations of iced aerofoil
NACA 64618

7. Luleå University of Technology
March 14, 2017
Luleå University of Technology
Influence of icing on the modal behavior of blades
Clean aerofoil case

8. Aeroelastic damping with icing
March 14, 2017
Luleå University of Technology
Aeroelastic damping with icing

9. Luleå University of Technology
March 14, 2017
Luleå University of Technology
Influence of icing on blade natural frequencies ##
Ice accumulation on wind turbine blades reduces its natural frequencies and each frequency reduce differently based on the location and quantity of ice mass
This behavior of natural frequencies can be used to detect and monitor ice growth on the wind turbine blades
## Brenner, D. Determination of the actual ice mass on wind turbine blades Measurements and methods for avoiding excessive icing loads threads, WinterWind, Åre, February 9, 2016.

10. Experimental modal analysis with added masses Natural frequency (Hz)
March 14, 2017
Luleå University of Technology
Experimental modal analysis with added masses
Vibration mode
Natural frequency (Hz)
Case 1
Case 2
Case 3
Case 4
1st Flap
20.0
20.0 (-0.00%)
19.7 (-1.50%)
18.4 (-8.00%)
2nd Flap
125.9
124.7 (-0.95%)
118.4 (-5.96%)
122.8 (-2.46%)
3rd Flap
348.8
334.7 (-4.04%)
341.6 (-2.06%)
342.2 (-1.89%)
Each frequency reduce differently with the location of added mass.

11. Neural network for inverse problem
March 14, 2017
Luleå University of Technology
Neural network for inverse problem f1 f2 f3 m1 m2 m3
An Artificial Neural Network model is trained with a dataset of natural frequencies of the structure calculated with different added masses at different locations

12. Luleå University of Technology
March 14, 2017
Luleå University of Technology
Identification of added mass on a cantilever beam in experiments
A cantilever beam is divided into three zones and an added mass of zero or some mass value in each zone creates 7 possible cases
Cases 1-7 in the below figure considers 0 or 11 g added mass on the cantilever beam
Cases 8-14 in the below figure considers 0 or 27 g added mass on the cantilever beam
Natural frequencies of the beam in these cases are estimated from experiments and given as an input to the trained neural network model
Added masses identified in 14 test cases using natural frequencies estimated from experiments

13. Luleå University of Technology
March 14, 2017
Luleå University of Technology
Application of the technique to detect ice mass on a wind turbine blade
Ice accumulation on a wind turbine blade can be approximated in terms of three masses that are distributed with constant linear mass density along the blade length
Wind turbine blade natural frequencies are calculated using its FEM model considering different values of ice masses in the three different zones defined on the blade
An Artificial Neural Network (ANN) model is trained with the dataset of natural frequencies and added masses
ANN approximates the nonlinear relation between ice masses and blade natural frequencies
Once the network is trained, it can be used to detect ice masses for any given set of natural frequencies of the iced blade
The detection technique requires first few natural frequencies of the blade as an input and these can be estimated from the blade’s vibration measurements

14. Artificial Neural Network model for ice mass detection
March 14, 2017
Luleå University of Technology
Artificial Neural Network model for ice mass detection
An Artificial Neural Network model is trained with a data set of blade natural frequencies calculated using its FEM model considering different ice masses in the three zones defined on the blade
Trained neural network model is tested with the blade natural frequencies corresponding to four test cases shown in the below figure and the identified ice masses are compared in below table with the actual ice masses used in the calculations
Note: WAPE means weighted average percentage error defined as the ratio of sum of the absolute error in the identified masses to the sum of actual ice masses
Table
The proposed detection technique identifies ice masses roughly

15. Luleå University of Technology
March 14, 2017
Luleå University of Technology
Future plan
To analyze modal behavior, ambient vibration response, loads acting on the NREL 5 MW wind turbine blade using the aerodynamic behavior of iced aerofoils simulated using CFD
Building a small experimental wind turbine set-up to demonstrate the proposed ice detection technique

16. Luleå University of Technology
March 14, 2017
Luleå University of Technology
Thank You