# New Assessment Scales for Evaluating the Degree of Risk of Wind Turbine Blade Damage Caused by Terrain-Induced Turbulence

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## Abstract

**:**

## 1. Introduction

## 2. Overview of the Kushikino Reimei Wind Farm

## 3. In-Situ Data Analysis

#### 3.1. Analysis of Wind Turbine Power Output Data

#### 3.2. Analysis of Wind Turbine Alarm Data

- (1)
- Shutdown due to excessive yaw error (definition: malfunctions occur due to deviation of the nacelle direction and the anemoscope direction).
- (2)
- Discordance in wind directions of sensors for wind direction and speed (definition: malfunctions occur due to disagreement in the values of the two sensors).

#### 3.3. Analysis of Nacelle Propeller-Vane Anemometer Data

#### 3.4. Analysis of Wind Turbine Blade Strain Data

- F
_{i}is the load of the i-th class of the fatigue load spectrum; - n
_{i}is the number of cycles in the i-th class of the fatigue load spectrum; - N is the equivalent of cycles;
- m is the S-N (stress-number of cycles to failure) curve slope for relevant material.
- N = 600 and m = 10 with fiber-reinforced plastic (FRP) blades in this study.

## 4. Numerical Simulation of Airflow with the WRF Mesoscale Model

## 5. Overview of the Numerical Simulation Method Based on Large-Eddy Simulation (RIAM-COMPACT)

#### 5.1. Setting of Numerical Parameters

_{in}represents streamwise wind velocity of the inlet boundary at the maximum altitude point, and ν represents the coefficient of kinematic viscosity. On the basis of the two types of reference scales, the dimensionless parameter, Re, is the Reynolds number (= U

_{in}h/ν). For this simulation, Re = 10

^{4}. The time step was specified as Δt = 2 × 10

^{−3}h/U

_{in}. Furthermore, identical simulation conditions were applied to both northerly and easterly winds. In the present study, we used a vector-parallel supercomputer system named NEC SX-ACE. The NEC SX-ACE provides four cores per node. When using one node of this system, about 8 million grid points of LES simulation took several hours.

#### 5.2. Flow Visualization of Simulation Results

#### 5.3. Proposal of Turbulence Evaluation Index (Uchida-Kawashima Scale_1)

_{in}

_{,}wind velocity at the maximum height above the ground of the inflow boundary, as shown in Figure 15. Instead of the average wind velocity at the hub height, the U

_{in}inflow velocity at the inflow boundary is used for normalization; the formula is generalized and does not depend on wind directions or terrain undulations.

#### 5.4. Analysis of Turbulence Statistics and Uchida-Kawashima Scale_1 Verification Part 1

#### 5.5. Mt. Benzaiten Impact Assessment and Uchida-Kawashima Scale_1 Verification Part 2

## 6. In-situ Data Analysis of Impacts of Terrain-induced Turbulence on Fatigue Damage in Wind Turbine Blades

#### 6.1. Relationship between Wind Speed and its Standard Deviation and Damage Equivalent Load (DEL)

#### 6.2. Investigation Regarding Accumulated Fatigue Damage of Wind Turbine Blades

- U-K scale_2 > 1.0: more than the design value, impact of the terrain-induced turbulence: large.
- U-K scale_2 ≦ 1.0: design value and less, impact of terrain-induced turbulence: small.

## 7. A Proposal for the Use of the U-K Scales and Future Research

## 8. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 7.**Comparison between theoretical data and measured data for wind turbine #10. (

**a**) Northerly wind. (

**b**) Easterly wind.

**Figure 8.**Result of graphing the values in Table 3. (

**a**) Number of alarm occurrences for yaw misalignment. (

**b**) Number of alarm occurrences for wind direction mismatch of the wind vane. Note: Wind turbine systems resort to shutting down the wind turbine if the yaw misalignment exceeds a threshold.

**Figure 9.**Frequency distribution of the direction of the 10-min average wind (%): (

**a**) wind rose (frequency distribution) and the average of the 10-min average wind speed observed for 16 wind directions (m/s): (

**b**) wind speed by direction (wind measurement height: hub height (60 m), analysis period: 3 November 2015, 0:00 a.m. JST–17 March 2016, 7:00 a.m. JST).

**Figure 10.**Relationship between the standard deviation and the average of the wind speed in 10-min periods for two wind directions (wind measurement height: hub-height (60 m), analysis period: 3 November 2015, 0:00 a.m. JST–17 March 2016, 7:00 a.m. JST). (

**a**) Northerly wind. (

**b**) Easterly wind.

**Figure 11.**Relationship between turbulence intensity and the average of the wind speed in 10-min periods for two wind directions (wind measurement height: hub-height (60 m), analysis period: 3 November 2015, 0:00 a.m. JST–17 March 2016, 7:00 a.m. JST). (

**a**) Northerly wind. (

**b**) Easterly wind.

**Figure 12.**Blade strain data (blade flapwise bending raw data). (

**a**) Northerly wind. (

**b**) Easterly wind. Note: interval: 0.02 seconds, average wind speed: approx. 9 m/s.

**Figure 13.**Time series of wind speed, standard deviation and normalized damage equivalent load (DEL) for flapwise blade bending. Plotted values were evaluated from instantaneous data values within 10-min periods. (

**a**) Northerly wind. (

**b**) Easterly wind.

**Figure 15.**Distribution of the horizontal wind vectors in Domain 4, approximately 60 m above the ground surface. 9:40 a.m. JST, Nov. 13, 2015.

**Figure 20.**Distribution of the streamwise wind velocity component on a vertical cross-section that includes wind turbine #10 and the instantaneous flow field. (

**a**) Northerly wind. (

**b**) Easterly wind.

**Figure 21.**Time-series data of streamwise wind velocity from the numerical simulations. Red: northerly wind, Blue: easterly wind.

**Figure 22.**Vertical profiles of the streamwise wind velocity at wind turbine #10, with a time-averaged flow field. Red: northerly wind, Blue: easterly wind.

**Figure 23.**Vertical profiles of the non-dimensional standard deviations at wind turbine #10, with a time-averaged flow field. Red: northerly wind, Blue: easterly wind. (

**a**) Streamwise direction. (

**b**) Spanwise direction. (

**c**) Vertical direction.

**Figure 24.**Distribution of the streamwise wind velocity component on a vertical cross-section, which includes wind turbine #10 and wind velocity vectors at wind turbine #10, easterly wind, and instantaneous flow field.

**Figure 26.**Relationship between standard deviation (m/s) and damage equivalent load (DEL). (

**a**) Northerly wind. (

**b**) Easterly wind.

**Figure 28.**An example of wind energy resource assessment based on the two reference scales (the U-K scales).

**Table 1.**Elevation information for wind turbine #10 and distance between Mt. Benzaiten (elevation 519 m) and wind turbine #10.

Elevation at Base of Wind Turbine #10 | Maximum Blade Tip Elevation (Above Sea Level) | Distance Between Mt. Benzaiten and Wind Turbine #10 |
---|---|---|

418 m | 518 m | Approx. 300 m |

Alarm Item | Wind Turbine #10 | Other Wind Turbines (Average) |
---|---|---|

Shutdown due to excessive yaw error | 1448 | 530 |

Discordance in wind directions of sensors | 308 | 80 |

Alarm Item | N | NNE | NE | ENE | E | ESE | SE | SSE | |

Shutdown due to excessive yaw error | 39 | 12 | 130 | 150 | 560 | 176 | 58 | 18 | |

Discordance in wind directions of sensors | 5 | 2 | 33 | 35 | 146 | 45 | 16 | 10 | |

Alarm Item | S | SSW | SW | WSW | W | WNW | NW | NNW | Total |

Shutdown due to excessive yaw error | 11 | 7 | 2 | 2 | 8 | 2 | 158 | 115 | 1448 |

Discordance in wind directions of sensors | 6 | 0 | 0 | 1 | 1 | 2 | 3 | 3 | 308 |

**Table 4.**Frequency distribution of the direction of the 10-min average wind (%) and the average of the 10-min average wind speed observed for 16 directions (wind measurement height: hub height (60 m), analysis period: 3 November 2015, 0:00 a.m. JST–17 March 2016, 7:00 a.m. JST).

Height | Item | N | NNE | NE | ENE | E | ESE | SE | SSE | S | SSW | SW | WSW | W | WNW | NW | NNW | Total |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|

60 m | Frequency Distribution (%) | 22.5 | 13.8 | 5.6 | 4.0 | 4.4 | 3.6 | 7.5 | 4.3 | 3.0 | 2.2 | 1.2 | 0.9 | 1.3 | 1.8 | 12.6 | 11.2 | 100.0 |

Average Wind Speed (m/s) | 6.1 | 5.8 | 4.8 | 4.1 | 4.5 | 4.7 | 6.7 | 6.0 | 5.1 | 5.0 | 5.0 | 3.0 | 4.6 | 5.0 | 9.2 | 6.6 | 6.1 |

Wind Direction Range | Total Number of 10-min Periods for Which Wind Statistics are Calculated | |
---|---|---|

Northerly Wind | 0° ± 15° | 4036 (Total: 12,567; 32.1%) |

Easterly Wind | 90° ± 15° | 496 (Total: 12,567; 4.0%) |

**Table 6.**Comparison of the values of the U-K Scale_1 at wind turbine hub height (z* = 60 m) under different N values.

N = 4.0 | N = 7.0 | N = 10.0 | Criteria of the U-K Scale_1 | |
---|---|---|---|---|

Northerly Wind | 0.16 | 0.17 | 0.17 | 0.20 |

Easterly Wind | 0.24 | 0.25 | 0.24 |

Easterly Wind, N = 7.0 | Criteria of the U-K Scale_1 | |
---|---|---|

Case of Removing Mt. Benzaiten (elevation 519 m) | 0.01 | 0.20 |

Current Situation | 0.28 |

© 2019 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**

Uchida, T.; Kawashima, Y.
New Assessment Scales for Evaluating the Degree of Risk of Wind Turbine Blade Damage Caused by Terrain-Induced Turbulence. *Energies* **2019**, *12*, 2624.
https://doi.org/10.3390/en12132624

**AMA Style**

Uchida T, Kawashima Y.
New Assessment Scales for Evaluating the Degree of Risk of Wind Turbine Blade Damage Caused by Terrain-Induced Turbulence. *Energies*. 2019; 12(13):2624.
https://doi.org/10.3390/en12132624

**Chicago/Turabian Style**

Uchida, Takanori, and Yasushi Kawashima.
2019. "New Assessment Scales for Evaluating the Degree of Risk of Wind Turbine Blade Damage Caused by Terrain-Induced Turbulence" *Energies* 12, no. 13: 2624.
https://doi.org/10.3390/en12132624