WIND TURBINE LINEAR PARAMETER VARYING CONTROL USING FAST CODE Farzad A. Shirazi ∗ Dept. of Mechanical Engineering University of Houston Houston, TX 77204 Email: fashiraz@mail.uh.edu Karolos M. Grigoriadis Dept. of Mechanical Engineering University of Houston Houston, TX 77204 karolos@uh.edu Daniel Viassolo Vestas Technology R&D Americas Inc. Houston, TX 77002 davia@vestas.com ABSTRACT Linear parameter varying (LPV) control of a three-bladed horizontal-axis wind turbine in partial and full load conditions using FAST code is presented. The multivariable LPV controller is designed for a lumped model of the wind turbine with five degrees-of-freedom consisting blades, drive-train and the tower. The controller is scheduled in real-time based on the mean wind speed. The objective is to minimize the H ∞ performance index from the wind turbulence to the controlled output vector. The closed-loop responses of the LPV controller are compared with a traditional PI-scheduled controller in the FAST/Simulink envi- ronment for the NREL 5MW baseline wind turbine. Compared to the PI-scheduled controller, the LPV design reduced the tran- sient loads in switching between partial to full load regions of the operation. The fluctuations of the generator speed and torque are decreased resulting in a smoother power generation. The wind turbine structural loads in terms of blade root flap-wise bending moments and tower fore-aft bending moment are mitigated in different loading conditions. 1 Introduction Wind turbine technology has been advancing rapidly in last decades while new challenges are appearing for the future growth of the technology. The size of wind turbines has been steadily increasing over the past years resulting in larger and heavier de- sign of the subsystems and higher mechanical loads on the tur- bine. In addition, force/moment sensing or accelerometers can now be installed on blades as well as the nacelle and tower to improve controllability. Design of novel advanced multivari- able controllers are in need to increase the power capture and reduce fatigue loads on the wind turbine structure. However, in ∗ Address all correspondence to this author. most of the current commercial systems simplistic single-input- single-output (SISO) gain-scheduled proportional-integral (PI) controllers are still being used for control [9, 10]. Advanced con- trol techniques that take benefit of the multi-input-multi-output (MIMO) nature of these systems are essential to accommodate coupling between loops [4, 6]. Optimal controllers based on linear quadratic Gaussian (LQG) design have been examined in [12]. Robust MIMO control of blade pitch angles and the generator torque has also been studied recently [3, 6]. Gain- Scheduled H ∞ control via LMI techniques has been designed and implemented in [11]. Linear parameter varying (LPV) controllers have been pro- posed to cope with the nonlinear parameter-varying dynamics of wind turbines in partial and full load conditions [2, 13]. LPV controllers have been shown to be very effective in improving closed-loop performance in different operating regions, as well as, addressing robustness [3, 13, 15]. It is common in the liter- ature to design LPV controllers for the linearized model of the wind turbine and then simulate them on the original nonlinear lumped model. However in our approach, for the first time, the multivariable LPV controllers for the full operating region of a wind turbine are validated using FAST (Fatigue, Aerodynamics, Structures, and Turbulence) code environment and the closed- loop responses are compared with a conventional PI-scheduled controller. The wind turbine under study is a 5MW onshore three- bladed horizontal axis turbine which its technical information is provided by the DOE National Renewable Energy Lab (NREL) [9]. The FAST code is a comprehensive aeroelastic simulator ca- pable of predicting both the extreme and fatigue loads of two- and three-bladed horizontal-axis wind turbines (HAWTs) [8]. FAST is considered as a standard wind turbine dynamic simu- lation tool in industry and will be used in this work to validate ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference DSCC2012-MOVIC2012 1 Copyright © 2012 by ASME DSCC2012-MOVIC2012-8558 October 17-19, 2012, Fort Lauderdale, Florida, USA Downloaded From: http://proceedings.asmedigitalcollection.asme.org/ on 12/20/2013 Terms of Use: http://asme.org/terms