Global sensitivity analysis of wind turbine power output

Wind Energy ◽  
2013 ◽  
Vol 17 (7) ◽  
pp. 983-995 ◽  
Author(s):  
Phillip M. McKay ◽  
Rupp Carriveau ◽  
David S-K. Ting ◽  
Jennifer L. Johrendt
Keyword(s):  
Sensitivity Analysis ◽  
Wind Turbine ◽  
Power Output ◽  
Global Sensitivity Analysis ◽  
Global Sensitivity

Global sensitivity analysis of the blade geometry variables on the wind turbine performance

Wind Energy ◽  
2017 ◽  
Vol 20 (9) ◽  
pp. 1601-1616 ◽  
Author(s):  
Fernando Echeverría ◽  
Fermín Mallor ◽  
Unai San Miguel
Keyword(s):  
Sensitivity Analysis ◽  
Wind Turbine ◽  
Global Sensitivity Analysis ◽  
Global Sensitivity ◽  
Turbine Performance ◽  
Blade Geometry

scholarly journals Global sensitivity analysis of offshore wind turbine foundation fatigue loads

2019 ◽  
Vol 140 ◽  
pp. 177-189 ◽  
Author(s):  
Joey Velarde ◽  
Claus Kramhøft ◽  
John Dalsgaard Sørensen
Keyword(s):  
Sensitivity Analysis ◽  
Wind Turbine ◽  
Global Sensitivity Analysis ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Global Sensitivity ◽  
Fatigue Loads

scholarly journals Global Sensitivity Analysis of High Speed Shaft Subsystem of a Wind Turbine Drive Train

2018 ◽  
Vol 2018 ◽  
pp. 1-20
Author(s):  
Saeed Asadi ◽  
Viktor Berbyuk ◽  
Håkan Johansson
Keyword(s):  
Sensitivity Analysis ◽  
Wind Turbine ◽  
High Speed ◽  
Global Sensitivity Analysis ◽  
Structural Parameters ◽  
Drive Train ◽  
Lagrangian Formalism ◽  
Objective Functions ◽  
Global Sensitivity ◽  
Turbine Drive

The wind turbine dynamics are complex and critical area of study for the wind industry. Quantification of the effective factors to wind turbine performance is valuable for making improvements to both power performance and turbine health. In this paper, the global sensitivity analysis of validated mathematical model for high speed shaft drive train test rig has been developed in order to evaluate the contribution of systems input parameters to the specified objective functions. The drive train in this study consists of a 3-phase induction motor, flexible shafts, shafts’ coupling, bearing housing, and disk with an eccentric mass. The governing equations were derived by using the Lagrangian formalism and were solved numerically by Newmark method. The variance based global sensitivity indices are introduced to evaluate the contribution of input structural parameters correlated to the objective functions. The conclusion from the current research provides informative beneficial data in terms of design and optimization of a drive train setup and also can provide better understanding of wind turbine drive train system dynamics with respect to different structural parameters, ultimately designing more efficient drive trains. Finally, the proposed global sensitivity analysis (GSA) methodology demonstrates the detectability of faults in different components.

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