Maximizing the overall production of wind farms by setting the individual operating point of wind turbines

The classical operation strategy of wind farms seeks each wind turbine to convert as much aerodynamic power as available from the incoming airflow. But this does not warranty that the power converted by the whole wind farm be a maximum due to the interaction between turbines (wake effect). Unlike the conventional operation, this paper proposes the individual selection of the operation point of each turbine so that the overall production of the wind farm is maximized. To reach that goal, the power produced by some upwind turbines is slightly reduced in order to increase the available aerodynamic power for the downwind turbines, which results in an increase of the overall wind farm energy extraction. The optimization is performed by means of a genetic algorithm that selects the optimal pitch angle and tip speed ratio of each individual wind turbine, in order to maximize the overall wind farm production.

[1]  G. P. Corten.  More Power and Less Loads in Wind Farms: ' Heat and Flux' , 2004 .

[2]  Jan-Willem van Wingerden,et al.  A model-free distributed approach for wind plant control , 2013, 2013 American Control Conference.

[3]  N. J. Tarp-Johansen,et al.  Effective turbulence models and fatigue reliability in wind farms , 2008 .

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

[5]  Rebecca J. Barthelmie,et al.  Analytical modelling of wind speed deficit in large offshore wind farms , 2006 .

[6]  M Maarten Steinbuch,et al.  Optimal control of wind power plants , 1988 .

[7]  S. Frandsen.  Turbulence and turbulence-generated structural loading in wind turbine clusters , 2007 .

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

[9]  Amy Stidworthy,et al.  TOPFARM - next generation design tool for optimisation of wind farm topology and operation , 2011 .

[10]  María Isabel Blanco.  The economics of wind energy , 2009 .

[11]  Daria Madjidian,et al.  A Stationary Turbine Interaction Model for Control of Wind Farms , 2011 .

[12]  M. Y. Hussaini,et al.  Placement of wind turbines using genetic algorithms , 2005 .

[13]  Sancho Salcedo-Sanz,et al.  Seeding evolutionary algorithms with heuristics for optimal wind turbines positioning in wind farms , 2011 .

[14]  Kincho H. Law,et al.  Wind farm power maximization based on a cooperative static game approach , 2013, Smart Structures.

[15]  Jun Wang,et al.  Optimal Micro-siting of Wind Farms by Particle Swarm Optimization , 2010, ICSI.

[16]  Julio Hernández,et al.  Survey of modelling methods for wind turbine wakes and wind farms , 1999 .

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

[18]  Johan Meyers,et al.  Analysis of turbulent flow properties and energy fluxes in optimally controlled wind-farm boundary layers , 2014 .

[19]  M. Payán,et al.  Overall design optimization of wind farms , 2011 .

[20]  Luciano Castillo,et al.  Unrestricted wind farm layout optimization (UWFLO): Investigating key factors influencing the maximum power generation , 2012 .

[21]  M. Burgos Payán,et al.  Optimum design of transmissions systems for offshore wind farms including decision making under risk , 2013 .

[22]  B. Lange,et al.  Comparison of Wake Model Simulations with Offshore Wind Turbine Wake Profiles Measured by Sodar , 2006 .

[23]  Eunkuk Son,et al.  Blade pitch angle control for aerodynamic performance optimization of a wind farm , 2013 .