Comparison of Strategies for Enhancing Energy Capture and Reducing Loads Using LIDAR and Feedforward Control

In this paper, we investigate strategies to enhance turbine energy capture and mitigate fatigue loads using pulsed light detection and ranging (LIDAR) system-enabled torque control strategies. To enhance energy capture when a turbine is operating below rated wind speed, three advanced LIDAR-enabled torque controllers are proposed: the disturbance tracking control (DTC) augmented with LIDAR, the optimally tracking rotor (OTR) control augmented with LIDAR, and LIDAR-based preview control. The DTC with LIDAR and LIDAR-based preview control is combined with a linear quadratic regulator in the feedback path, while OTR is a strategy adapted from a quadratic kΩ2 torque feedback control. These control strategies are simulated in turbulent wind files and their performance is compared against the baseline kΩ2 control scheme. We also consider the effects of different LIDAR update rates and range gates. It is shown that LIDAR-enabled controllers have only a small effect on energy capture at the cost of increased control action and low-speed shaft torque load. However, when considering a combination of fatigue load mitigation, power capture enhancement, and control authority requirements, the LIDAR-enabled preview controller outperforms the baseline kΩ2 controller.

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

[2]  Kathryn E. Johnson,et al.  A tutorial on the dynamics and control of wind turbines and wind farms , 2009, 2009 American Control Conference.

[3]  Alan Wright,et al.  Adding Feedforward Blade Pitch Control for Load Mitigation in Wind Turbines: Non-Causal Series Expansion, Preview Control, and Optimized FIR Filter Methods , 2011 .

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

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

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

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

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

[9]  Torben Mikkelsen,et al.  Determining the Velocity Fine Structure by a Laser Anemometer with Fixed Orientation , 2011 .

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

[11]  Cole Boulevard,et al.  Disturbance Tracking and Blade Load Control of Wind Turbines in Variable-Speed Operation , 2003 .

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

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

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

[15]  Paul Fleming,et al.  Resonant Vibrations Resulting from the Re-Engineering of a Constant-Speed 2-Bladed Turbine to a Variable-Speed 3-Bladed Turbine , 2010 .

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

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

[18]  Michel Verhaegen,et al.  Feedback–feedforward individual pitch control for wind turbine load reduction , 2009 .

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

[20]  P. W. Carlin,et al.  Results from the NREL Variable-Speed Test bed , 1998 .

[21]  N. Kelley.  A Case for Including Atmospheric Thermodynamic Variables in Wind Turbine Fatigue Loading Parameter Identification , 1999 .

[22]  Neil Kelley,et al.  Overview of the TurbSim Stochastic Inflow Turbulence Simulator: Version 1.21 (Revised February 1, 2001) , 2007 .

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

[24]  M. Hand,et al.  Lidar for Turbine Control: March 1, 2005 - November 30, 2005 , 2006 .

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

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

[27]  Torben Mikkelsen,et al.  On mean wind and turbulence profile measurements from ground-based wind lidars: limitations in time and space resolution with continuous wave and pulsed lidar systems , 2009 .

[28]  Lucy Y. Pao,et al.  LIDAR Wind Speed Measurements of Evolving Wind Fields , 2012 .