Nonlinear pitch control design for load reduction on wind turbines

Author(s):  
Shuai Xiao ◽  
Geng Yang ◽  
Hua Geng
2008 ◽  
Vol 130 (3) ◽  
Author(s):  
M. Geyler ◽  
P. Caselitz

This paper deals with multivariable pitch control design for wind turbines, including load reducing control objectives. Different design approaches, including collective and cyclic pitch, and robustness aspects are discussed. A control design with decoupled controllers for collective and cyclic pitch is worked out in detail, based on the H∞ norm minimization approach. The control design is verified by simulations with a full nonlinear model of the wind turbine, showing the potential of multivariable pitch control to actively increase damping of the first axial tower bending mode and to reduce 1p fluctuations in blade root bending moments. Multivariable control design provides a convenient way of including additional load reducing objectives into the pitch controller of wind turbines. Fatigue loading of certain components, as tower and blades, could be reduced significantly.


Wind Energy ◽  
2014 ◽  
Vol 18 (4) ◽  
pp. 677-697 ◽  
Author(s):  
E. van Solingen ◽  
J.W. van Wingerden

Author(s):  
Daniel Ossmann ◽  
Julian Theis ◽  
Peter Seiler

The increasing size of modern wind turbines also increases the structural loads on the turbine caused by effects like turbulence or asymmetries in the inflowing wind field. Consequently, the use of advanced control algorithms for active load reduction has become a relevant part of current wind turbine control systems. In this paper, an H∞-norm optimal multivariable control design approach for an individual blade-pitch control law is presented. It reduces the structural loads both on the rotating and non-rotating parts of the turbine. Classical individual blade-pitch control strategies rely on single control loops with low bandwidth. The proposed approach makes it possible to use a higher bandwidth since it takes into account coupling at higher frequencies. A controller is designed for the utility-scale 2.5 MW Liberty research turbine operated by the University of Minnesota. Stability and performance are verified using a high-fidelity nonlinear benchmark model.


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