Reliability assessment of generic geared wind turbines by GTST-MLD model and Monte Carlo simulation

Abstract : In the last decade, the installed capacity of wind turbines has increased far more than other renewable energy sources such as solar, biomass or geothermal. As for any energy equipment, reliability is the fundamental attribute that needs to be guaranteed. A number of studies have been carried out for wind turbine reliability assessment. Most of them model the wind turbine system as a whole, without investigating its interior structure and failure logic. In this paper, a modeling and simulation framework is proposed for the reliability assessment of generic geared wind turbine systems. It is based on a Goal Tree, Success Tree and Master Logic Diagram for modeling the relationships among components and functions in a wind turbine system, and the impact of factors and mechanisms influencing the failure of the components. The modeling framework is customized to represent the strength of the relationships and the uncertainty of the impact of failures of these components on other components and functions. The model is eventually integrated in a Monte Carlo simulation framework for the computation of the wind turbine system reliability. Finally, model validation is performed by comparing the simulation results with those obtained by a Bayesian network model developed for this purpose.
Document type :
Journal articles
Complete list of metadatas

Cited literature [7 references]  Display  Hide  Download

https://hal-supelec.archives-ouvertes.fr/hal-01176996
Contributor : Yanfu Li <>
Submitted on : Thursday, July 16, 2015 - 1:29:06 PM
Last modification on : Thursday, April 5, 2018 - 12:30:14 PM
Long-term archiving on : Saturday, October 17, 2015 - 11:03:51 AM

File

Reliability Analysis of a Wind...
Files produced by the author(s)

Identifiers

Citation

Yan-Fu Li, S. Valla, Enrico Zio. Reliability assessment of generic geared wind turbines by GTST-MLD model and Monte Carlo simulation. Renewable Energy, Elsevier, 2015, 83, pp.222-233. ⟨10.1016/j.renene.2015.04.035⟩. ⟨hal-01176996⟩

Share

Metrics

Record views

218

Files downloads

206