Data-driven repetitive control

Wind tunnel experiments under turbulent conditions

Journal article (2018)

Authors

J.A. Frederik Team Jan-Willem van Wingerden - Mechanical, Maritime and Materials Engineering

Lars Kröger University of Oldenburg

Gerd Gülker University of Oldenburg

J.W. van Wingerden Team Jan-Willem van Wingerden - Mechanical, Maritime and Materials Engineering

Research Group

Team Jan-Willem van Wingerden (Mechanical, Maritime and Materials Engineering) (TU Delft)

DOI: https://doi.org/10.1016/j.conengprac.2018.08.011

Wind energy Load alleviation Subspace identification Data-driven control Individual pitch control Active grid Repetitive control Wind tunnel experiments

To reference this document use:

http://resolver.tudelft.nl/uuid:4de6e270-7db6-445f-b2a5-0b7846a2fdbe

More Info

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Published Date

2018

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Jan-Willem van Wingerden

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.

Files

CEP_DRC_Frederik2.pdf

(pdf | 2.04 Mb)

- Embargo expired in 29-08-2020