Preventing wind turbine overspeed in highly turbulent wind events using disturbance accommodating control and light detection and ranging

Light detection and ranging (LIDAR) systems can be used to provide wind inflow information to a wind turbine controller before the wind reaches the turbine. Both fatigue and extreme load reduction are possible as a result; in this research, we propose a LIDAR-based controller designed to prevent emergency shutdowns caused by rotor overspeed. This switching controller consists of a disturbance accommodating control (DAC)-based baseline controller and a different DAC linearized about a reduced generator speed for extreme events, also referred to as an extreme event controller. Switching between the controllers was performed using linear interpolation over various transition times, depending on how early the extreme event could be detected. If a gust of wind is detected using LIDAR measurements evaluated by a one-sided cumulative summation algorithm, a relatively long transition time can be used. Switching can also be based on a large output estimation error, ey, in which case the transition time is shorter. Once the extreme event passed, control is switched from the extreme event controller back to the baseline DAC. This switching controller resulted in fewer overspeeds when compared with the modified baseline controller, which is a gain scheduled DAC. By preventing overspeeds, the switching controller increased the mean power the wind turbine generated over a simulated 10 min period. Copyright © 2014 John Wiley & Sons, Ltd.

[1]  Stoyan Kanev,et al.  Wind turbine extreme gust control , 2010 .

[2]  Poul Ejnar Sørensen,et al.  Control design for a pitch-regulated, variable speed wind turbine , 2005 .

[3]  K. A. Stol,et al.  Wind Turbine Field Testing of State-Space Control Designs: August 25, 2003--November 30, 2003 , 2004 .

[4]  G. S. Bir,et al.  User's Guide to MBC3: Multi-Blade Coordinate Transformation Code for 3-Bladed Wind Turbine , 2010 .

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

[6]  Kathryn E. Johnson,et al.  LIDAR-based FX-RLS feedforward control for wind turbine load mitigation , 2011, Proceedings of the 2011 American Control Conference.

[7]  Kathryn E. Johnson,et al.  Development, implementation, and testing of fault detection strategies on the National Wind Technology Center’s controls advanced research turbines , 2011 .

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

[9]  A. D. Wright,et al.  Modern Control Design for Flexible Wind Turbines , 2004 .

[10]  A. D. Wright,et al.  Advanced Control Design for Wind Turbines; Part I: Control Design, Implementation, and Initial Tests , 2008 .

[11]  C. D. Johnson,et al.  Theory of Distrubance-Accommodating Controllers , 1976 .

[12]  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 .

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

[14]  Herbert J. Sutherland,et al.  On the Fatigue Analysis of Wind Turbines , 1999 .

[15]  Neil Kelley,et al.  Analysis of Wind Speed Measurements using Continuous Wave LIDAR for Wind Turbine Control y , 2011 .

[16]  B. Jonkman Turbsim User's Guide: Version 1.50 , 2009 .

[17]  Alan Wright,et al.  The use of preview wind measurements for blade pitch control , 2011 .

[18]  Iker Elorza,et al.  On the feasibility and limits of extreme load reduction for wind turbines via advanced sensing: A LIDAR case study , 2013, 2013 American Control Conference.

[19]  Jason Jonkman,et al.  Dynamics Modeling and Loads Analysis of an Offshore Floating Wind Turbine , 2007 .

[20]  Manfred Morari,et al.  A unified framework for the study of anti-windup designs , 1994, Autom..

[21]  David Schlipf,et al.  Field Testing LIDAR Based Feed-Forward Controls on the NREL Controls Advanced Research Turbine , 2013 .

[22]  G. Taylor The Spectrum of Turbulence , 1938 .

[23]  L Y Pao,et al.  Control of Wind Turbines , 2011, IEEE Control Systems.