Reliability-based design optimization of wind turbine drivetrain with integrated multibody gear dynamics simulation considering wind load uncertainty

2017 ◽  
Vol 56 (1) ◽  
pp. 183-201 ◽  
Author(s):  
Huaxia Li ◽  
Hyunkyoo Cho ◽  
Hiroyuki Sugiyama ◽  
K. K. Choi ◽  
Nicholas J. Gaul
Keyword(s):  
Wind Turbine ◽  
Design Optimization ◽  
Wind Load ◽  
Dynamics Simulation ◽  
Reliability Based Design Optimization ◽  
Load Uncertainty ◽  
Gear Dynamics ◽  
Reliability Based Design ◽  
Wind Load Uncertainty

Numerical Procedure for Design Optimization of Wind Turbine Drivetrain Using Multibody Gear Dynamics Simulation Considering Wind Load Uncertainty

2016 ◽  
Author(s):  
Huaxia Li ◽  
Hiroyuki Sugiyama ◽  
Hyunkyoo Cho ◽  
K. K. Choi ◽  
Nicholas J. Gaul
Keyword(s):  
Wind Turbine ◽  
Design Optimization ◽  
Gear Tooth ◽  
Numerical Procedure ◽  
Wind Load ◽  
Rolling Contact ◽  
Dynamics Simulation ◽  
Load Uncertainty ◽  
Gear Dynamics ◽  
Wind Load Uncertainty

An accurate prediction of the service life of wind turbine drivetrains is crucial to ensure safe and reliable operation. In particular, gear teeth of the wind turbine multi-stage drivetrain experience severe cyclic rolling contact resulting from highly variable wind loads which are stochastic in nature. Thus, the failure rate of the gearbox is reported to be higher than other wind turbine components. Despite many studies on gear contact and failure analysis of wind turbine drivetrains, limited studies have been carried out regarding gear design optimization considering wind load uncertainty. For this reason, in this study, an integrated multibody gear dynamics simulation procedure for design optimization of the wind turbine drivetrain considering the wide spatiotemporal wind load uncertainty is developed. To this end, the wind load uncertainty model using the joint probability density function of the ten-minute mean wind speed and turbulence intensity, rotor blade aerodynamics, drivetrain dynamics considering the detailed gear tooth contact geometry including the profile modification, and probabilistic contact fatigue failure model are integrated for use in the gear tooth design optimization of wind turbine drivetrains to ensure the expected design life. Several numerical examples are presented to demonstrate the numerical procedure developed in this study.

scholarly journals Reliability-based design optimization of offshore wind turbine support structures using analytical sensitivities and factorized uncertainty modeling

2019 ◽  
Author(s):  
Lars Einar S. Stieng ◽  
Michael Muskulus
Keyword(s):  
Wind Turbine ◽  
Design Optimization ◽  
Optimization Methods ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
High Fidelity ◽  
Reliability Based Design Optimization ◽  
Support Structure ◽  
Reliability Based Design ◽  
Gradient Based

Abstract. The need for cost effective support structure designs for offshore wind turbines has led to continued interest in the development of design optimization methods. So far, almost no studies have considered the effect of uncertainty, and hence probabilistic constraints, on the support structure design optimization problem. In this work, we present a general methodology that implements recent developments in gradient-based design optimization, in particular the use of analytical gradients, within the context of reliability-based design optimization methods. By an assumed factorization of the uncertain response into a design-independent, probabilistic part and a design-dependent, but completely deterministic part, it is possible to computationally decouple the reliability analysis from the design optimization. Furthermore, this decoupling makes no further assumption about the functional nature of the stochastic response, meaning that high fidelity surrogate modeling through Gaussian process regression of the probabilistic part can be performed while using analytical gradient-based methods for the design optimization. We apply this methodology to several different cases based around a uniform cantilever beam and the OC3 Monopile and different loading and constraints scenarios. The results demonstrate the viability of the approach in terms of obtaining reliable, optimal support structure designs and furthermore show that in practice only a limited amount of additional computational effort is required compared to deterministic design optimization. While there are some limitations in the applied cases, and some further refinement might be necessary for applications to high fidelity design scenarios, the demonstrated capabilities of the proposed methodology show that efficient reliability-based optimization for offshore wind turbine support structures is feasible.

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