Calculating wind turbine component loads for improved life prediction

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

Research output: Contribution to journalArticleAcademicpeer-review

31 Downloads (Pure)

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

@article{1f74988bb82d49d7b7080d6f2cd75044,
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.",
keywords = "Aerodynamic imbalance, Load based maintenance, Physical model, Rotor loads, Wind turbine",
author = "D.P. Rommel and {Di Maio}, D. and T. Tinga",
year = "2020",
month = "2",
day = "1",
doi = "10.1016/j.renene.2019.06.131",
language = "English",
volume = "146",
pages = "223--241",
journal = "Renewable energy",
issn = "0960-1481",
publisher = "Elsevier",

}

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

TY - JOUR

T1 - Calculating wind turbine component loads for improved life prediction

AU - Rommel, D.P.

AU - Di Maio, D.

AU - Tinga, T.

PY - 2020/2/1

Y1 - 2020/2/1

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.

KW - Aerodynamic imbalance

KW - Load based maintenance

KW - Physical model

KW - Rotor loads

KW - Wind turbine

UR - http://www.scopus.com/inward/record.url?scp=85068165467&partnerID=8YFLogxK

U2 - 10.1016/j.renene.2019.06.131

DO - 10.1016/j.renene.2019.06.131

M3 - Article

VL - 146

SP - 223

EP - 241

JO - Renewable energy

JF - Renewable energy

SN - 0960-1481

ER -