Data-driven repetitive control: Wind tunnel experiments under turbulent conditions

Joeri Frederik, Lars Kröger, Gerd Gülker, Jan Willem van Wingerden

Research output: Contribution to journalArticleScientificpeer-review

11 Citations (Scopus)
1 Downloads (Pure)

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.

Original languageEnglish
Pages (from-to)105-115
JournalControl Engineering Practice
Volume80
DOIs
Publication statusPublished - 2018

Keywords

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

Fingerprint Dive into the research topics of 'Data-driven repetitive control: Wind tunnel experiments under turbulent conditions'. Together they form a unique fingerprint.

Cite this