Wind turbine gearbox reliability verification by multivariate Gaidai reliability method

Abstract

Reliability research is essential since WT (Wind turbines) are built to endure high wind and wave-induced stresses. Novel multivariate and 2D (bivariate) reliability methods presented in this investigation being conceived by authors to assist designers in accurately assessment of crucial stressors, acting inside key mechanical WT parts, such as gearbox and drivetrain. Current study made use of the recently created 2D modified Weibull-type approach. Since multivariate statistical analysis takes into consideration cross-correlations between various system components, it is more suited for design than univariate statistical analysis. To cross-validate 10-MW semi-submersible type FWT (i.e., Floating Wind Turbine) gearbox system failure or damage probability, forecasted by the multivariate Gaidai reliability methodology, current study employed 2D modified Weibull approach. Typical load types that FWTs and related parts are prone, include longitudinal, bending, twisting, and cyclic stresses.Stochastic nature of environmental loads, acting on FWTs in terms of windspeed, direction, shear, vorticity may cause excessive nonlinear structural dynamic effects, hence multivariate reliability analysis for FWT key components like gearbox and drivetrain is necessary. In this investigation dynamic, structural, aerodynamic, and control aspects of the FWT system had been modeled, using advanced numerical techniques – FWT drivetrain dynamics has been modeled utilizing SIMPACK (Multibody Simulation Method) software. Novel multivariate Gaidai risk assessment approach provided a reliable reliability evaluation for the coupled drivetrain's dynamics, given design return periods of interest.Weakness of bivariate approach has been highlighted, comprehensive solution has been presented in a form of novel multivariate reliability method.

Keywords

• Floating wind turbine
• Green energy
• Wind turbine
• Sustainability
• Renewable energy