The helix approach: using dynamic individual pitch control to enhance wake mixing in wind farms

Wind farm control using dynamic concepts is a research topic that is receiving an increasing amount of interest. The main concept of this approach is that dynamic variations of the wind turbine control settings lead to higher wake turbulence, and subsequently faster wake recovery due to increased mixing. As a result, downstream turbines experience higher wind speeds, thus increasing their energy capture. The current state of the art in dynamic wind farm control is to vary the magnitude of the thrust force of an upstream turbine. Although very effective, this approach also leads to increased power and thrust variations, negatively impacting energy quality and fatigue loading. In this paper, a novel approach for the dynamic control of wind turbines in a wind farm is proposed: using individual pitch control, the fixed-frame tilt and yaw moments on the turbine are varied, thus dynamically manipulating the wake. This strategy is named the helix approach since the resulting wake has a helical shape. Large eddy simulations of a two-turbine wind farm show that the helix approach leads to enhanced wake mixing with minimal power and thrust variations.

[1]  Ryozo Nagamune,et al.  A quantitative review of wind farm control with the objective of wind farm power maximization , 2019, Journal of Wind Engineering and Industrial Aerodynamics.

[2]  Niko Mittelmeier,et al.  Effects of axial induction control on wind farm energy production - A field test , 2019, Renewable Energy.

[3]  Filippo Campagnolo,et al.  Periodic dynamic induction control of wind farms: proving the potential in simulations and wind tunnel experiments , 2019, Wind Energy Science.

[4]  Sanjiva K. Lele,et al.  Wind farm power optimization through wake steering , 2019, Proceedings of the National Academy of Sciences.

[5]  Y. Matsuo,et al.  Forced wake meandering for rapid recovery of velocity deficits in a wind turbine wake , 2019, AIAA Scitech 2019 Forum.

[6]  Jan-Willem van Wingerden,et al.  Analysis and optimal individual pitch control decoupling by inclusion of an azimuth offset in the multi-blade coordinate transformation , 2018, Wind Energy.

[7]  Jennifer Annoni,et al.  Analysis of control-oriented wake modeling tools using lidar field results , 2018, Wind Energy Science.

[8]  Jan-Willem van Wingerden,et al.  Data-driven repetitive control: Wind tunnel experiments under turbulent conditions , 2018, Control Engineering Practice.

[9]  Johan Meyers,et al.  Towards practical dynamic induction control of wind farms: analysis of optimally controlled wind-farm boundary layers and sinusoidal induction control of first-row turbines , 2018, Wind Energy Science.

[10]  Michael Hölling,et al.  Validating subspace predictive repetitive control under turbulent wind conditions with wind tunnel experiment , 2018, Journal of Physics: Conference Series.

[11]  Johan Meyers,et al.  Dynamic Strategies for Yaw and Induction Control of Wind Farms Based on Large-Eddy Simulation and Optimization , 2018 .

[12]  Mario A. Rotea,et al.  Model-free control of wind farms: A comparative study between individual and coordinated extremum seeking , 2017 .

[13]  Jennifer Annoni,et al.  A tutorial on control-oriented modeling and control of wind farms , 2017, 2017 American Control Conference (ACC).

[14]  Jennifer Annoni,et al.  Field test of wake steering at an offshore wind farm , 2017 .

[15]  J. Meyers,et al.  An optimal control framework for dynamic induction control of wind farms and their interaction with the atmospheric boundary layer , 2017, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[16]  Andrew Ning,et al.  Maximization of the annual energy production of wind power plants by optimization of layout and yaw‐based wake control , 2017 .

[17]  F. Porté-Agel,et al.  Experimental and theoretical study of wind turbine wakes in yawed conditions , 2016, Journal of Fluid Mechanics.

[18]  Johan Meyers,et al.  Effect of wind turbine response time on optimal dynamic induction control of wind farms , 2016 .

[19]  Martin Kühn,et al.  Estimating the wake deflection downstream of a wind turbine in different atmospheric stabilities: an LES study , 2016 .

[20]  Filippo Campagnolo,et al.  Wind tunnel testing of a closed-loop wake deflection controller for wind farm power maximization , 2016 .

[21]  David Schlipf,et al.  Lidar-based wake tracking for closed-loop wind farm control , 2016 .

[22]  J. W. van Wingerden,et al.  A predictive control framework for optimal energy extraction of wind farms , 2016 .

[23]  Johan Meyers,et al.  Wake structure in actuator disk models of wind turbines in yaw under uniform inflow conditions , 2016 .

[24]  Carlo L. Bottasso,et al.  Wind tunnel testing of wake control strategies , 2016, 2016 American Control Conference (ACC).

[25]  Jennifer Annoni,et al.  Analysis of axial‐induction‐based wind plant control using an engineering and a high‐order wind plant model , 2016 .

[26]  J. Meyers,et al.  Optimal control of energy extraction in wind-farm boundary layers , 2015, Journal of Fluid Mechanics.

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

[28]  Kathryn E. Johnson,et al.  Evaluating techniques for redirecting turbine wakes using SOWFA , 2014 .

[29]  Kathryn E. Johnson,et al.  Simulation comparison of wake mitigation control strategies for a two‐turbine case , 2015 .

[30]  Robert Flemming Mikkelsen,et al.  Large-eddy simulations of the Lillgrund wind farm , 2013 .

[31]  Jason R. Marden,et al.  A Model-Free Approach to Wind Farm Control Using Game Theoretic Methods , 2013, IEEE Transactions on Control Systems Technology.

[32]  L. Henriksen,et al.  The DTU 10-MW Reference Wind Turbine , 2013 .

[33]  J. Michalakes,et al.  A numerical study of the effects of atmospheric and wake turbulence on wind turbine dynamics , 2012 .

[34]  E. Migoya,et al.  Application of a LES technique to characterize the wake deflection of a wind turbine in yaw , 2009 .

[35]  G. Bir Multi-Blade Coordinate Transformation and its Application to Wind Turbine Analysis , 2008 .

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

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

[38]  Jens Nørkær Sørensen,et al.  Numerical Modeling of Wind Turbine Wakes , 2002 .

[39]  J. Højstrup,et al.  A Simple Model for Cluster Efficiency , 1987 .

[40]  N. Jensen A note on wind generator interaction , 1983 .

[41]  P. Lissaman Energy Effectiveness of Arbitrary Arrays of Wind Turbines , 1979 .