Overcoming fundamental limitations of wind turbine individual blade pitch control with inflow sensors

Individual pitch control (IPC) provides an important means of attenuating harmful fatigue and extreme loads upon the load bearing structures of a wind turbine. Conventional IPC architectures determine the additional pitch demand signals required for load mitigation in response to measurements of the flap-wise blade-root bending moments. However, the performance of such architectures is fundamentally limited by bandwidth constraints imposed by the blade dynamics. Seeking to overcome this problem, we present a simple solution based upon a local blade inflow measurement on each blade. Importantly, this extra measurement enables the implementation of an additional cascaded feedback controller that overcomes the existing IPC performance limitation and hence yields significantly improved load reductions. Numerical demonstration upon a high-fidelity and nonlinear wind turbine model reveals (i) 60% reduction in the amplitude of the dominant 1P fatigue loads, and (ii) 59% reduction in the amplitude of extreme wind shear induced blade loads, compared to a conventional IPC controller with the same robust stability margin. This paper therefore represents a significant alternative to wind turbine IPC load mitigation as compared to LiDAR-based feedforward control approaches.

[1]  Michael Amitay,et al.  Active Enhancement of Wind Turbine Blades Performance , 2008 .

[2]  Niels N. Sørensen,et al.  The DAN-AERO MW Experiments , 2010 .

[3]  René Bos,et al.  Assessing the Severity of Wind Gusts with Lidar , 2016, Remote. Sens..

[4]  Ervin Bossanyi,et al.  Individual Blade Pitch Control for Load Reduction , 2003 .

[5]  Ervin Bossanyi,et al.  Wind Turbine Control for Load Reduction , 2003 .

[6]  Karl Stol,et al.  A Comparison of Multi-Blade Coordinate Transformation and Direct Periodic Techniques for Wind Turbine Control Design , 2009 .

[7]  Kathryn E. Johnson,et al.  Lidar-enhanced wind turbine control: Past, present, and future , 2016, 2016 American Control Conference (ACC).

[8]  Niels Kjølstad Poulsen,et al.  Individual pitch control of wind turbines using local inflow measurements , 2008 .

[9]  Niels Kjølstad Poulsen,et al.  Individual pitch control using LIDAR measurements , 2012, 2012 IEEE International Conference on Control Applications.

[10]  William Leithead,et al.  Alleviation of unbalanced rotor loads by single blade controllers , 2009 .

[11]  Torben J. Larsen,et al.  Active load reduction using individual pitch, based on local blade flow measurements , 2005 .

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

[13]  Arne V. Johansson,et al.  Pressure fluctuation in high-Reynolds-number turbulent boundary layer: results from experiments and DNS , 2012 .

[14]  G.A.M. van Kuik,et al.  Review of state of the art in smart rotor control research for wind turbines , 2010 .

[15]  Lars Christian Henriksen,et al.  Sensor comparison study for load alleviating wind turbine pitch control , 2014 .

[16]  B. Ll. Jones,et al.  Real‐time wind field reconstruction from LiDAR measurements using a dynamic wind model and state estimation , 2016 .

[17]  Ervin Bossanyi,et al.  Further load reductions with individual pitch control , 2005 .

[18]  Paul S. Veers,et al.  Load Mitigation with Bending/Twist-coupled Blades on Rotors using Modern Control Strategies , 2003 .

[19]  Adam Niesłony,et al.  Determination of fragments of multiaxial service loading strongly influencing the fatigue of machine components , 2009 .

[20]  Matthew A. Lackner,et al.  A comparison of smart rotor control approaches using trailing edge flaps and individual pitch control , 2009 .

[21]  J. W. van Wingerden,et al.  Linear individual pitch control design for two‐bladed wind turbines , 2015 .

[22]  N. Jenkins,et al.  Wind Energy Handbook: Burton/Wind Energy Handbook , 2011 .

[23]  P. Caselitz,et al.  Robust Multivariable Pitch Control Design for Load Reduction on Large Wind Turbines , 2008 .

[24]  E. Bossanyi,et al.  Field Test Results with Individual Pitch Control on the NREL CART3 Wind Turbine , 2012 .

[25]  Scott J. Johnson,et al.  An overview of active load control techniques for wind turbines with an emphasis on microtabs , 2010 .

[26]  Torben Mikkelsen,et al.  A spinner‐integrated wind lidar for enhanced wind turbine control , 2013 .

[27]  Qian Lu,et al.  Fundamental performance similarities between individual pitch control strategies for wind turbines , 2017, Int. J. Control.

[28]  J. Jonkman,et al.  Definition of a 5-MW Reference Wind Turbine for Offshore System Development , 2009 .

[29]  Eric C. Kerrigan,et al.  Aerodynamic load control in horizontal axis wind turbines with combined aeroelastic tailoring and trailing‐edge flaps , 2016 .

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

[31]  Marcias Martinez,et al.  Load monitoring for active control of wind turbines , 2015 .

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

[33]  W.E. Leithead,et al.  A novel approach to structural load control using intelligent actuators , 2009, 2009 17th Mediterranean Conference on Control and Automation.

[34]  Robert L. Nelson,et al.  A Smart Wind Turbine Blade Using Distributed Plasma Actuators for Improved Performance , 2008 .

[35]  Keith Glover,et al.  A loop-shaping design procedure using H/sub infinity / synthesis , 1992 .

[36]  Carlo L. Bottasso,et al.  LiDAR-enabled model predictive control of wind turbines with real-time capabilities , 2014 .

[37]  Tae Tom Oomen,et al.  Subspace predictive repetitive control to mitigate periodic loads on large scale wind turbines , 2014 .

[38]  B. Ll. Jones,et al.  Analysis and design of Coleman transform‐based individual pitch controllers for wind‐turbine load reduction , 2015 .