Calculating wind turbine component loads for improved life prediction

D.P. Rommel*, D. Di Maio, T. Tinga

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

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    Abstract

    Wind turbines life time is commonly predicted based on statistical methods. However, the success of statistics-based maintenance depends on the amount of variation in the system design, usage and load. Life time prediction based on physical models seeks to overcome this drawback by considering the actual design and evaluating the specific usage, load and operating condition of the considered systems. In this paper, a load-based maintenance approach is proposed to predict wind turbines life time. Physical models are used to evaluate load profiles at wind turbine blade root, rotor hub center and tower head. The effects of surface roughness, side winds, yaw misalignment, rotor tilt and blade cone angle, individual blade pitching and wind turbulences are considered and quantified. It is shown that centrifugal, gravity, Euler and Coriolis accelerations dominate the blade root loads. Tilt and cone angle, as well as individual blade pitching, affect the rotor hub and dynamic tower head loads. Further, the actual wind speed distribution is considered which is also proven to be a critical life time prediction parameter. Finally, a set of parameters is proposed that need to be monitored in a specific wind turbine to enable the practical implementation of a predictive maintenance policy.

    Original languageEnglish
    Pages (from-to)223-241
    Number of pages19
    JournalRenewable energy
    Volume146
    DOIs
    Publication statusPublished - 1 Feb 2020

    Fingerprint

    Turbine components
    Wind turbines
    Turbomachine blades
    Rotors
    Towers
    Cones
    Statistical methods
    Gravitation
    Turbulence
    Surface roughness
    Systems analysis
    Statistics

    Keywords

    • Aerodynamic imbalance
    • Load based maintenance
    • Physical model
    • Rotor loads
    • Wind turbine

    Cite this

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    title = "Calculating wind turbine component loads for improved life prediction",
    abstract = "Wind turbines life time is commonly predicted based on statistical methods. However, the success of statistics-based maintenance depends on the amount of variation in the system design, usage and load. Life time prediction based on physical models seeks to overcome this drawback by considering the actual design and evaluating the specific usage, load and operating condition of the considered systems. In this paper, a load-based maintenance approach is proposed to predict wind turbines life time. Physical models are used to evaluate load profiles at wind turbine blade root, rotor hub center and tower head. The effects of surface roughness, side winds, yaw misalignment, rotor tilt and blade cone angle, individual blade pitching and wind turbulences are considered and quantified. It is shown that centrifugal, gravity, Euler and Coriolis accelerations dominate the blade root loads. Tilt and cone angle, as well as individual blade pitching, affect the rotor hub and dynamic tower head loads. Further, the actual wind speed distribution is considered which is also proven to be a critical life time prediction parameter. Finally, a set of parameters is proposed that need to be monitored in a specific wind turbine to enable the practical implementation of a predictive maintenance policy.",
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    author = "D.P. Rommel and {Di Maio}, D. and T. Tinga",
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    day = "1",
    doi = "10.1016/j.renene.2019.06.131",
    language = "English",
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    Calculating wind turbine component loads for improved life prediction. / Rommel, D.P.; Di Maio, D.; Tinga, T.

    In: Renewable energy, Vol. 146, 01.02.2020, p. 223-241.

    Research output: Contribution to journalArticleAcademicpeer-review

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    AU - Rommel, D.P.

    AU - Di Maio, D.

    AU - Tinga, T.

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    N2 - Wind turbines life time is commonly predicted based on statistical methods. However, the success of statistics-based maintenance depends on the amount of variation in the system design, usage and load. Life time prediction based on physical models seeks to overcome this drawback by considering the actual design and evaluating the specific usage, load and operating condition of the considered systems. In this paper, a load-based maintenance approach is proposed to predict wind turbines life time. Physical models are used to evaluate load profiles at wind turbine blade root, rotor hub center and tower head. The effects of surface roughness, side winds, yaw misalignment, rotor tilt and blade cone angle, individual blade pitching and wind turbulences are considered and quantified. It is shown that centrifugal, gravity, Euler and Coriolis accelerations dominate the blade root loads. Tilt and cone angle, as well as individual blade pitching, affect the rotor hub and dynamic tower head loads. Further, the actual wind speed distribution is considered which is also proven to be a critical life time prediction parameter. Finally, a set of parameters is proposed that need to be monitored in a specific wind turbine to enable the practical implementation of a predictive maintenance policy.

    AB - Wind turbines life time is commonly predicted based on statistical methods. However, the success of statistics-based maintenance depends on the amount of variation in the system design, usage and load. Life time prediction based on physical models seeks to overcome this drawback by considering the actual design and evaluating the specific usage, load and operating condition of the considered systems. In this paper, a load-based maintenance approach is proposed to predict wind turbines life time. Physical models are used to evaluate load profiles at wind turbine blade root, rotor hub center and tower head. The effects of surface roughness, side winds, yaw misalignment, rotor tilt and blade cone angle, individual blade pitching and wind turbulences are considered and quantified. It is shown that centrifugal, gravity, Euler and Coriolis accelerations dominate the blade root loads. Tilt and cone angle, as well as individual blade pitching, affect the rotor hub and dynamic tower head loads. Further, the actual wind speed distribution is considered which is also proven to be a critical life time prediction parameter. Finally, a set of parameters is proposed that need to be monitored in a specific wind turbine to enable the practical implementation of a predictive maintenance policy.

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