# A Parameter Selection Method for Wind Turbine Health Management through SCADA Data

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## Abstract

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## 1. Introduction

## 2. Methodology

#### 2.1. Mathematical Definition of Copulas

#### 2.2. Mutual Information (MI) and Entropy

_{i}, i = 1,2,…,n as

_{i}) means the probability of each value of X. It can be extended to a continuous random variable scenario as

#### 2.3. Estimate Mutual Information through Copula

#### 2.4. Empirical Copula-Based Mutual Information Estimation (ECMI)

## 3. Application: Feature Extraction from Wind Turbine SCADA Data

#### 3.1. Scenario Description

#### 3.2. Results Based on ECMI

#### 3.3. Comparison Study: The Advantages of Mutual Information Based Parameter Selection

- Select 10 parameters which rank higher in the three rank lists.
- Whenever there are several parameters regarding to the same sub component, choose the one which ranks higher.

## 4. Conclusions

## Author Contributions

## Conflicts of Interest

## References

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**Figure 4.**Cumulative copula distribution of the two parameters. In both figures, X and Y axis represent the bins in [0, 1] and Z axis shows the probability distribution of the copula distribution of the two parameters. In (

**a**), the two parameters are active power and wind speed; while in (

**b**) the two parameters are active power and yaw.

**Figure 5.**Copula density of the two parameters. In both figures, X and Y axis represent the bins in [0, 1] and Z axis shows the probability of the copula distribution of the two parameters. In (

**a**) the two parameters are active power and wind speed; while in (

**b**) the two parameters are active power and yaw.

**Figure 6.**Best validation performance with three approaches through NN training process. While (

**a**) represent the result based on the PCCA list; (

**b**) shows the result based on the KCCA list; (

**c**) displays the result based on the ECMI list.

Rank | Parameter |
---|---|

1. | Generator_Speed |

2. | Rotor_Speed |

3. | Yaw |

4. | Wind_Speed |

5. | Pitch_L2 |

6. | Pitch_L1 |

7. | Pitch_L3 |

8. | Generator_Torque |

9. | Generator_U1T |

10. | Generator_W2T |

11. | Generator_V1T |

12. | Generator_V2T |

13. | Generator_U2T |

14. | Generator_W1T |

15. | Converter_GridT |

16. | Generator_BearingT2 |

17. | Generator_Fan2T |

18. | Gearbox_BearingT1 |

19. | Gearbox_BearingT2 |

20. | Gearbox_OilT |

21. | Converter_Temperature |

22. | Generator_Fan1T |

23. | Generator_BearingT1 |

24. | Gearbox_EntranceT |

25. | Gearbox_BearingT |

26. | Nacelle_Temperature |

27. | Pitch_1V |

28. | Pitch_2V |

29. | Pitch_3V |

30. | Ambient_Temperature |

31. | Converter_LV |

32. | Converter_LC |

33. | Wind Turbine_State |

34. | Gearbox_Oilpressure |

35. | Wind_Direction |

Rank | PCCA | KCCA |
---|---|---|

1. | Converter_L Current | Generator_Torque |

2. | Generator_Torque | Converter_L Current |

3. | Wind_Speed | Generator_Speed |

4. | Generator_U1T | Rotor_Speed |

5. | Generator_W2T | Wind_Speed |

6. | Generator_V2T | Gearbox_BearingT1 |

7. | Generator_U2T | Gearbox_BearingT2 |

8. | Generator_V1T | Generator_U1T |

9. | Generator_W1T | Generator_W2T |

10. | Gearbox_BearingT1 | Generator_U2T |

11. | Gearbox_BearingT2 | Generator_V2T |

12. | Generator_Speed | Generator_V1T |

13. | Rotor_Speed | Generator_W1T |

14. | Converter_Temperature | Pitch_L3 |

15. | Gearbox_OilT | Pitch_L2 |

16. | Generator_Fan2T | Pitch_L1 |

17. | Generator_BearingT2 | Gearbox_OilT |

18. | Gearbox_EntranceT | Gearbox_Oilpressure |

19. | Gearbox_BearingT | Generator_Fan2T |

20. | Generator_BearingT1 | Converter_Temperature |

21. | Gearbox_Oilpressure | Wind Turbine_State |

22. | Pitch_3V | Generator_BearingT2 |

23. | Pitch_2V | Gearbox_EntranceT |

24. | Pitch_1V | Gearbox_BearingT |

25. | Converter_GridT | Generator_BearingT1 |

26. | Converter_LV | Generator_Fan1T |

27. | Generator_Fan1T | Converter_LV |

28. | Wind_Direction | Pitch_3V |

29. | Nacelle_Temperature | Pitch_2V |

30. | Yaw | Pitch_1V |

31. | Ambient_Temperature | Converter_GridT |

32. | Wind Turbine_State | Wind_Direction |

33. | Pitch_L2 | Yaw |

34. | Pitch_L1 | Nacelle_Temperature |

35. | Pitch_L3 | Ambient_Temp. |

No. | PCCA | KCCA | ECMI |
---|---|---|---|

1. | Converter_L Current | Generator_Torque | Generator_Speed |

2. | Generator_Torque | Converter_L Current | Rotor_Speed |

3. | Wind_Speed | Generator_Speed | Yaw |

4. | Generator_U1T | Wind_Speed | Wind_Speed |

5. | Gearbox_Bearing T1 | Gearbox_Bearing T1 | Pitch_L2 |

6. | Generator_Speed | Generator_U1T | Generator_Torque |

7. | Rotor_Speed | Pitch_L3 | Generator_U1T |

8. | ConverterTemperature | Gearbox_OilT | GeneratorBearingT2 |

9. | Gearbox_OilT | Gearbox_Oilpressure | Generator_Fan2T |

10. | Generator_Fan2T | Generator_Fan2T | Gearbox_Bearing T2 |

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Du, M.; Yi, J.; Mazidi, P.; Cheng, L.; Guo, J. A Parameter Selection Method for Wind Turbine Health Management through SCADA Data. *Energies* **2017**, *10*, 253.
https://doi.org/10.3390/en10020253

**AMA Style**

Du M, Yi J, Mazidi P, Cheng L, Guo J. A Parameter Selection Method for Wind Turbine Health Management through SCADA Data. *Energies*. 2017; 10(2):253.
https://doi.org/10.3390/en10020253

**Chicago/Turabian Style**

Du, Mian, Jun Yi, Peyman Mazidi, Lin Cheng, and Jianbo Guo. 2017. "A Parameter Selection Method for Wind Turbine Health Management through SCADA Data" *Energies* 10, no. 2: 253.
https://doi.org/10.3390/en10020253