Wind tunnel tests with combined pitch and free-floating flap control: data-driven iterative feedforward controller tuning

Journal Article (2016)
Author(s)

S.T. Navalkar (TU Delft - Team Raf Van de Plas)

L.O. Bernhammer (TU Delft - Wind Energy)

J. Sodja (TU Delft - Aerospace Structures & Computational Mechanics)

E. van Solingen

G.A.M. van Kuik (TU Delft - Wind Energy)

J.W. van Wingerden (TU Delft - Team Raf Van de Plas)

Research Group
Team Raf Van de Plas
Copyright
© 2016 S.T. Navalkar, L.O. Bernhammer, J. Sodja, E. van Solingen, G.A.M. van Kuik, J.W. van Wingerden
DOI related publication
https://doi.org/10.5194/wes-1-205-2016
More Info
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Publication Year
2016
Language
English
Copyright
© 2016 S.T. Navalkar, L.O. Bernhammer, J. Sodja, E. van Solingen, G.A.M. van Kuik, J.W. van Wingerden
Research Group
Team Raf Van de Plas
Issue number
2
Volume number
1
Pages (from-to)
205-220
Reuse Rights

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Abstract

Wind turbine load alleviation has traditionally been addressed in the literature using either full-span pitch control, which has limited bandwidth, or trailing-edge flap control, which typically shows low control authority due to actuation constraints. This paper combines both methods and demonstrates the feasibility and advantages of such a combined control strategy on a scaled prototype in a series of wind tunnel tests. The pitchable blades of the test turbine are instrumented with free-floating flaps close to the tip, designed such that they aerodynamically magnify the low stroke of high-bandwidth actuators. The additional degree of freedom leads to aeroelastic coupling with the blade flexible modes. The inertia of the flaps was tuned such that instability occurs just beyond the operational envelope of the wind turbine; the system can however be stabilised using collocated closed-loop control. A feedforward controller is shown to be capable of significant reduction of the deterministic loads of the turbine. Iterative feedforward tuning, in combination with a stabilising feedback controller, is used to optimise the controller online in an automated manner, to maximise load reduction. Since the system is non-linear, the controller gains vary with wind speed; this paper also shows that iterative feedforward tuning is capable of generating the optimal gain schedule online.