Abstract
An increasing number of wind turbines implement individual blade pitch control (IPC) to reduce turbine dynamic loading, and thereby, to reduce the capital and operational costs associated with energy production. The aim of this paper is to demonstrate IPC on a wind turbine prototype, in a model-free data-driven manner and with reduced pitch activity. For this, subspace predictive repetitive control (RC) is used, which combines online system identification with the continuous implementation of RC to form a fully adaptive control law. The controller is tested on a scaled two-bladed wind turbine with active pitchable blades, placed in an open-jet wind tunnel. Substantial load reductions to an extent of 68% are observed, and strict control over actuator signal frequency content is achieved. The control law also demonstrates the ability to adjust to changes in system dynamics while maintaining a high degree of load alleviation.
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