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A Control Strategy to Maximise Energy Extraction in Windfarms

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Bokharaie,  VS
Research Group Neuronal Convergence, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Bokharaie, V., & Meyers, J. (2016). A Control Strategy to Maximise Energy Extraction in Windfarms. 1-7.


Cite as: http://hdl.handle.net/21.11116/0000-0000-79CA-5
Abstract
The common practice in existing commercial windfarms is to set the control parameters of each individual wind turbine such that it extracts as much energy as possible from the wind, a setting that we refer to as greedy setting. But since each wind turbine reduces wind Velocity in its wake, downstream wind turbines will generate less power. In this study, using a Large Eddie Simulation (LES) environment, we show that if the operating points of some wind turbines are changed to non-greedy setting, the total energy extracted by windfarm can be increased. This holds when the control parameters are kept constant for relatively large time periods. In other words, it is possible to set the control parameters of some wind turbines in a windfarm such that the loss in energy extraction caused by deviating from greedy case is less than the gain in power generation in the wind turbines which are located downstream. We also present an optimisation scheme which is a step towards extending these results into a more dynamic approach to windfarm control.