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Sustainable Analysis of Wind Turbine Blade Fatigue: Simplified Method for Dynamic Load Measurement and Life Estimation

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  • Cristofer Aguilar Jiménez

    (Instituto de Investigación e Innovación en Energías Renovables, Universidad de Ciencias y Artes de Chiapas, Libramiento Norte Poniente 1150, Colonia Lajas Maciel, Tuxtla Gutiérrez 29039, Mexico)

  • Geovanni Hernández Gálvez

    (División de Ciencias Básicas e Ingeniería, Universidad Popular de la Chontalpa, Carretera Cárdenas-Huimanguillo km 2, Ranchería Paso y Playa, Cárdenas 86556, Mexico)

  • José Rafael Dorrego Portela

    (División de Estudios de Posgrado, Universidad del Istmo, Campus Tehuantepec, Ciudad Universitaria S/N, Barrio Santa Cruz, 4a. Sección, Santo Domingo, Tehuantepec 70760, Mexico)

  • Antonio Verde Añorve

    (Instituto de Investigación e Innovación en Energías Renovables, Universidad de Ciencias y Artes de Chiapas, Libramiento Norte Poniente 1150, Colonia Lajas Maciel, Tuxtla Gutiérrez 29039, Mexico)

  • Guillermo Ibáñez Duharte

    (Instituto de Investigación e Innovación en Energías Renovables, Universidad de Ciencias y Artes de Chiapas, Libramiento Norte Poniente 1150, Colonia Lajas Maciel, Tuxtla Gutiérrez 29039, Mexico)

  • Joel Pantoja Enríquez

    (Instituto de Investigación e Innovación en Energías Renovables, Universidad de Ciencias y Artes de Chiapas, Libramiento Norte Poniente 1150, Colonia Lajas Maciel, Tuxtla Gutiérrez 29039, Mexico)

  • Orlando Lastres Danguillecourt

    (Instituto de Investigación e Innovación en Energías Renovables, Universidad de Ciencias y Artes de Chiapas, Libramiento Norte Poniente 1150, Colonia Lajas Maciel, Tuxtla Gutiérrez 29039, Mexico)

  • Alberto-Jesus Perea-Moreno

    (Departamento de Física Aplicada, Radiología y Medicina Física, Campus Universitario de Rabanales, Universidad de Córdoba, 14071 Córdoba, Spain)

  • David Muñoz-Rodriguez

    (Departamento de Física Aplicada, Radiología y Medicina Física, Campus Universitario de Rabanales, Universidad de Córdoba, 14071 Córdoba, Spain)

  • Quetzalcoatl Hernandez-Escobedo

    (Escuela Nacional de Estudios Superiores Unidad Juriquilla, Universidad Nacional Autónoma de Mexico, Campus Juriquilla, Queretaron 76230, Mexico)

Abstract

This study presents a novel approach to addressing the challenges associated with wind turbine blade fatigue, focusing on the development of a simplified method for dynamic load measurement and life estimation. Wind turbine blades are subjected to complex and varied loads during their operational life, leading to fatigue-induced damage that can significantly impact the overall performance and longevity of the turbine. The proposed method integrates advanced sensor technologies and data analytics to capture dynamic loads on the blades more effectively. Dynamic load measurement and fatigue estimation for a wind turbine blade are quite challenging tasks, since the real-time wind-induced load is irregular and stochastic, and the associated load history affects blade fatigue life in complex ways. This paper shows the implementation of a simplified method for damage and life estimation of a 1.5 kW wind turbine blade with an aerodynamic stall-limiting system. The findings from this research contribute to advancing the field of wind energy by providing a streamlined and efficient approach to addressing blade fatigue issues, ultimately promoting the sustainable and economic utilization of wind power resources. The proposed method simplifies the processes of dynamic load measurement and fatigue life estimation by employing a resonance-based approach. This reduces energy and cost requirements compared to forced displacement methods, while maintaining accuracy in replicating damage equivalent loads. Additionally, it avoids the complexities of simulating real-world turbulence by using controlled conditions, ensuring reproducibility.

Suggested Citation

  • Cristofer Aguilar Jiménez & Geovanni Hernández Gálvez & José Rafael Dorrego Portela & Antonio Verde Añorve & Guillermo Ibáñez Duharte & Joel Pantoja Enríquez & Orlando Lastres Danguillecourt & Alberto, 2025. "Sustainable Analysis of Wind Turbine Blade Fatigue: Simplified Method for Dynamic Load Measurement and Life Estimation," Sustainability, MDPI, vol. 17(17), pages 1-30, August.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:17:p:7615-:d:1731052
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    References listed on IDEAS

    as
    1. Pacheco de Sá Sarmiento, Franciene Izis & Goes Oliveira, Jorge Luiz & Passos, Júlio César, 2022. "Impact of atmospheric stability, wake effect and topography on power production at complex-terrain wind farm," Energy, Elsevier, vol. 239(PC).
    2. Yang, Can & Xiao, Longfei & Deng, Shi & Chen, Peng & Liu, Lei & Cheng, Zhengshun, 2024. "An experimental study on the aerodynamic-induced effects of a semi-submersible floating wind turbine," Renewable Energy, Elsevier, vol. 222(C).
    3. Gruber, Katharina & Regner, Peter & Wehrle, Sebastian & Zeyringer, Marianne & Schmidt, Johannes, 2022. "Towards global validation of wind power simulations: A multi-country assessment of wind power simulation from MERRA-2 and ERA-5 reanalyses bias-corrected with the global wind atlas," Energy, Elsevier, vol. 238(PA).
    4. Lu, Liang & Wu, Haijun & Wu, Jianzhong, 2021. "A case study for the optimization of moment-matching in wind turbine blade fatigue tests with a resonant type exciting approach," Renewable Energy, Elsevier, vol. 174(C), pages 769-785.
    5. Cai, Wei & Hu, Yang & Fang, Fang & Yao, Lujin & Liu, Jizhen, 2023. "Wind farm power production and fatigue load optimization based on dynamic partitioning and wake redirection of wind turbines," Applied Energy, Elsevier, vol. 339(C).
    6. Kong, C. & Bang, J. & Sugiyama, Y., 2005. "Structural investigation of composite wind turbine blade considering various load cases and fatigue life," Energy, Elsevier, vol. 30(11), pages 2101-2114.
    7. Akpan, Anthony E. & Ben, Ubong C. & Ekwok, Stephen E. & Okolie, Chukwuma J. & Epuh, Emeka E. & Julzarika, Atriyon & Othman, Abdullah & Eldosouky, Ahmed M., 2024. "Technical and performance assessments of wind turbines in low wind speed areas using numerical, metaheuristic and remote sensing procedures," Applied Energy, Elsevier, vol. 357(C).
    8. de Aquino Ferreira, Saulo Custodio & Cyrino Oliveira, Fernando Luiz & Maçaira, Paula Medina, 2022. "Validation of the representativeness of wind speed time series obtained from reanalysis data for Brazilian territory," Energy, Elsevier, vol. 258(C).
    9. Kang, Yujoo & Kim, Hyebin & Lee, Sang, 2023. "Benefits of individual pitch control on offshore wind turbine submerged in upstream wake," Renewable Energy, Elsevier, vol. 217(C).
    10. He, Ruiyang & Yang, Hongxing & Sun, Shilin & Lu, Lin & Sun, Haiying & Gao, Xiaoxia, 2022. "A machine learning-based fatigue loads and power prediction method for wind turbines under yaw control," Applied Energy, Elsevier, vol. 326(C).
    11. Evans, S.P. & Bradney, D.R. & Clausen, P.D., 2018. "Assessing the IEC simplified fatigue load equations for small wind turbine blades: How simple is too simple?," Renewable Energy, Elsevier, vol. 127(C), pages 24-31.
    12. Patrick D. Moroney & Amrit Shankar Verma, 2023. "Durability and Damage Tolerance Analysis Approaches for Wind Turbine Blade Trailing Edge Life Prediction: A Technical Review," Energies, MDPI, vol. 16(24), pages 1-33, December.
    13. Pimenta, Francisco & Ribeiro, Daniel & Román, Adela & Magalhães, Filipe, 2024. "Predictive model for fatigue evaluation of floating wind turbines validated with experimental data," Renewable Energy, Elsevier, vol. 223(C).
    14. Chanprasert, W. & Sharma, R.N. & Cater, J.E. & Norris, S.E., 2022. "Large Eddy Simulation of wind turbine wake interaction in directionally sheared inflows," Renewable Energy, Elsevier, vol. 201(P1), pages 1096-1110.
    15. Chanprasert, W. & Sharma, R.N. & Cater, J.E. & Norris, S.E., 2022. "Large Eddy Simulation of wind turbine fatigue loading and yaw dynamics induced by wake turbulence," Renewable Energy, Elsevier, vol. 190(C), pages 208-222.
    16. Dai, Juchuan & Li, Mimi & Zhang, Fan & Zeng, Huifan, 2024. "Field load testing of wind turbines based on the relational model of strain vs load," Renewable Energy, Elsevier, vol. 221(C).
    Full references (including those not matched with items on IDEAS)

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