Data-driven repetitive control
Wind tunnel experiments under turbulent conditions
J.A. Frederik (TU Delft - Team Jan-Willem van Wingerden)
Lars Kröger (University of Oldenburg)
Gerd Gülker (University of Oldenburg)
J.W. Wingerden (TU Delft - Team Jan-Willem van Wingerden)
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Abstract
A commonly applied method to reduce the cost of wind energy, is alleviating the periodic loads on turbine blades using Individual Pitch Control (IPC). In this paper, a data-driven IPC methodology called Subspace Predictive Repetitive Control (SPRC) is employed. The effectiveness of SPRC will be demonstrated on a scaled 2-bladed wind turbine. An open-jet wind tunnel with an innovative active grid is employed to generate reproducible turbulent wind conditions. A significant load reduction with limited actuator duty is achieved even under these high turbulent conditions. Furthermore, it will be demonstrated that SPRC is able to adapt to changing operating conditions.
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