EconPapers    
Economics at your fingertips  
 

Calculating wind turbine component loads for improved life prediction

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

Renewable Energy, 2020, vol. 146, issue C, 223-241

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: Load based maintenance; Physical model; Wind turbine; Rotor loads; Aerodynamic imbalance (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148119309656
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:146:y:2020:i:c:p:223-241

DOI: 10.1016/j.renene.2019.06.131

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:renene:v:146:y:2020:i:c:p:223-241