Calculating wind turbine component loads for improved life prediction. (February 2020)
- Record Type:
- Journal Article
- Title:
- Calculating wind turbine component loads for improved life prediction. (February 2020)
- Main Title:
- Calculating wind turbine component loads for improved life prediction
- Authors:
- Rommel, D.P.
Di Maio, D.
Tinga, T. - Abstract:
- 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. Highlights: Generic physics-based model quantifies mechanical loads in drive train components. Quantifies effects of changes in environmental and operational conditions. Component life timeAbstract: 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. Highlights: Generic physics-based model quantifies mechanical loads in drive train components. Quantifies effects of changes in environmental and operational conditions. Component life time governed by design choices and calculated load profiles. Required measurements for life time prediction in real wind turbine are identified. … (more)
- Is Part Of:
- Renewable energy. Volume 146(2020)
- Journal:
- Renewable energy
- Issue:
- Volume 146(2020)
- Issue Display:
- Volume 146, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 146
- Issue:
- 2020
- Issue Sort Value:
- 2020-0146-2020-0000
- Page Start:
- 223
- Page End:
- 241
- Publication Date:
- 2020-02
- Subjects:
- Load based maintenance -- Physical model -- Wind turbine -- Rotor loads -- Aerodynamic imbalance
Renewable energy sources -- Periodicals
Power resources -- Periodicals
Énergies renouvelables -- Périodiques
Ressources énergétiques -- Périodiques
333.794 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09601481 ↗
http://www.elsevier.com/journals ↗
http://www.journals.elsevier.com/renewable-energy/ ↗ - DOI:
- 10.1016/j.renene.2019.06.131 ↗
- Languages:
- English
- ISSNs:
- 0960-1481
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7364.187000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 12087.xml