LIDAR-assisted preview controllers design for a MW-scale commercial wind turbine model

Existing commercial wind turbine control algorithms are typically feedback only. Nacelle-based commercial light detection and ranging (LIDAR) systems, which can detect preview wind information in front of the turbine to be used in feedforward controller design, can improve wind turbine control performance compared to a baseline standard proportional-integral (PI) feedback controller. Combined feedforward and feedback collective pitch control strategies are investigated in this research for both mitigating tower fore-aft fatigue load above rated wind speed and enhancing power capture below rated wind speed. When the wind speed is above rated, we consider a collective pitch LQ-based preview control scheme that augments the existing feedback controller and uses a Kalman filter in the control loop as the observer. When the wind speed is below rated, we combine a tower foreaft feedback damping pitch controller with a feedforward controller designed through the method of Lagrange multipliers optimization. Control effectiveness verifications are conducted through FAST simulations with multiple turbulent wind cases.

[1]  Alan Wright,et al.  Blade Pitch Control with Preview Wind Measurements y , 2010 .

[2]  Tim Fischer,et al.  Load analysis of look-ahead collective pitch control using LIDAR , 2010 .

[3]  Frank Allgöwer,et al.  Look-ahead cyclic pitch control using LIDAR , 2010 .

[4]  Neil Kelley,et al.  Model Predictive Control Using Preview Measurements From LIDAR y , 2011 .

[5]  Kathryn E. Johnson,et al.  Pulsed LIDAR-assisted Controllers for Turbine Power Capture Enhancement and Fatigue Load Mitigation Below Rated , 2012 .

[6]  David Schlipf,et al.  Nonlinear model predictive control of wind turbines using LIDAR , 2013 .

[7]  Torben Mikkelsen,et al.  Improving Yaw Alignment Using Spinner Based LIDAR , 2011 .

[8]  Kathryn E. Johnson,et al.  LIDAR-Based Extreme Event Control to Prevent Wind Turbine Overspeed , 2013 .

[9]  N. D. Kelley,et al.  Overview of the TurbSim Stochastic Inflow Turbulence Simulator: Version 1.10 , 2006 .

[10]  Torben Mikkelsen,et al.  Time series analysis of continuous-wave coherent Doppler Lidar wind measurements , 2008 .

[11]  Mark J. Balas,et al.  Disturbance Tracking Control Theory with Application to Horizontal Axis Wind Turbines , 1998 .

[12]  Masayoshi Tomizuka,et al.  Design of Digital Feedforward/Preview Controllers for Processes With Predetermined Feedback Controllers , 1980 .

[13]  Kathryn E. Johnson,et al.  FX-RLS-Based Feedforward Control for LIDAR-Enabled Wind Turbine Load Mitigation , 2012, IEEE Transactions on Control Systems Technology.

[14]  F. Dunne,et al.  LIDAR Wind Speed Measurement Analysis and Feed-Forward Blade Pitch Control for Load Mitigation in Wind Turbines , 2011 .

[15]  Kiyotsugu Takaba.  A tutorial on preview control systems , 2003, SICE 2003 Annual Conference (IEEE Cat. No.03TH8734).

[16]  Aleksander Hac.  Optimal Linear Preview Control of Active Vehicle Suspension , 1992 .

[17]  Darrell F. Socie,et al.  Simple rainflow counting algorithms , 1982 .

[18]  Torben Mikkelsen,et al.  Lidar wind speed measurements from a rotating spinner , 2010 .

[19]  L.Y. Pao,et al.  Control of variable-speed wind turbines: standard and adaptive techniques for maximizing energy capture , 2006, IEEE Control Systems.

[20]  Paul Fleming,et al.  Rotor Speed Dependent Yaw Control of Wind Turbines Based on Empirical Data , 2012 .

[21]  Alan Wright,et al.  Combining Standard Feedback Controllers with Feedforward Blade Pitch Control for Load Mitigation in Wind Turbines , 2010 .

[22]  David Schlipf,et al.  Prospects of a collective pitch control by means of predictive disturbance compensation assisted by wind speed measurements , 2008 .