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Operational Wind Turbine Blade Damage Evaluation Based on 10-min SCADA and 1 Hz Data

Author

Listed:
  • Antoine Chrétien

    (Department of Mechanical Engineering, École de Technologie Supérieure, Montreal, QC H3C 1K3, Canada)

  • Antoine Tahan

    (Department of Mechanical Engineering, École de Technologie Supérieure, Montreal, QC H3C 1K3, Canada)

  • Philippe Cambron

    (Department of Advanced Analytics Research, Power Factors, Brossard, QC J4Z 1A7, Canada)

  • Adaiton Oliveira-Filho

    (Department of Mechanical Engineering, École de Technologie Supérieure, Montreal, QC H3C 1K3, Canada)

Abstract

This work aims to propose a method enabling the evaluation of wind turbine blade damage and fatigue related to a 1 Hz wind speed signal applied to a large period and based on standard 10-min SCADA data. Previous studies emphasize the need for sampling with a 1 Hz frequency when carrying out blade damage computation. However, such methods cannot be applied to evaluate the damage for a long period of time due to the complexity of computation and data availability. Moreover, 1 Hz SCADA data are not commonly used in the wind farm industry because they require a large data storage capacity. Applying such an approach, which is based on a 1 Hz wind speed signal, to current wind farms is not a trivial pursuit. The present work investigates the possibility of overcoming the preceding issues by estimating the equivalent 1 Hz wind speed damage over a 10-min period characterized by SCADA data in terms of measured mean wind speed and turbulence intensity. Then, a discussion is carried out regarding a method to estimate the uncertainty of the simulation, in a bid to come up with a tool facilitating decision-making by the operator. A statistical analysis of the damage assessed for different wind turbines is thus proposed to determine which one has sustained the most damage. Finally, the probability of reaching a critical damage level over time is then proposed, allowing the operator to optimize the operating and maintenance schedule.

Suggested Citation

  • Antoine Chrétien & Antoine Tahan & Philippe Cambron & Adaiton Oliveira-Filho, 2023. "Operational Wind Turbine Blade Damage Evaluation Based on 10-min SCADA and 1 Hz Data," Energies, MDPI, vol. 16(7), pages 1-18, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:7:p:3156-:d:1112594
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    References listed on IDEAS

    as
    1. Mishnaevsky, Leon, 2019. "Repair of wind turbine blades: Review of methods and related computational mechanics problems," Renewable Energy, Elsevier, vol. 140(C), pages 828-839.
    2. Kim, Dae-Young & Kim, Yeon-Hee & Kim, Bum-Suk, 2021. "Changes in wind turbine power characteristics and annual energy production due to atmospheric stability, turbulence intensity, and wind shear," Energy, Elsevier, vol. 214(C).
    3. Jiang, Zhiyu & Xing, Yihan, 2022. "Load mitigation method for wind turbines during emergency shutdowns," Renewable Energy, Elsevier, vol. 185(C), pages 978-995.
    4. Hu, Weifei & Chen, Weiyi & Wang, Xiaobo & Jiang, Zhiyu & Wang, Yeqing & Verma, Amrit Shankar & Teuwen, Julie J.E., 2021. "A computational framework for coating fatigue analysis of wind turbine blades due to rain erosion," Renewable Energy, Elsevier, vol. 170(C), pages 236-250.
    5. Jannie S. Nielsen & John D. Sørensen, 2017. "Bayesian Estimation of Remaining Useful Life for Wind Turbine Blades," Energies, MDPI, vol. 10(5), pages 1-13, May.
    6. Vera-Tudela, Luis & Kühn, Martin, 2017. "Analysing wind turbine fatigue load prediction: The impact of wind farm flow conditions," Renewable Energy, Elsevier, vol. 107(C), pages 352-360.
    7. Zárate-Miñano, Rafael & Anghel, Marian & Milano, Federico, 2013. "Continuous wind speed models based on stochastic differential equations," Applied Energy, Elsevier, vol. 104(C), pages 42-49.
    8. Zhenye Sun & Matias Sessarego & Jin Chen & Wen Zhong Shen, 2017. "Design of the OffWindChina 5 MW Wind Turbine Rotor," Energies, MDPI, vol. 10(6), pages 1-20, June.
    9. Jang, Yun Jung & Choi, Chan Woong & Lee, Jang Ho & Kang, Ki Weon, 2015. "Development of fatigue life prediction method and effect of 10-minute mean wind speed distribution on fatigue life of small wind turbine composite blade," Renewable Energy, Elsevier, vol. 79(C), pages 187-198.
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