Turbine Wake Deflection Measurement in a Wind Tunnel with a Lidar WindScanner

Conference Paper


  • Abstract Wind turbines are typically closely spaced in wind farms, and thus operate in the wake of upstream turbines and experience power losses. Currently, one of the techniques to reduce the wake interaction between turbines within a wind farm is to yaw the upstream turbine with regards to the incident wind direction. The objective is to deflect the wake, which can potentially increase the overall power output and the annual energy production of the wind farm. Experimental data can aid the process to thoroughly analyse the wake deflection under different inflow conditions, which is necessary to apply a yaw-based wind farm control model. The aim of the present research is to investigate the possibility and accuracy of the experimental setup to measure the wake characteristics with a high spatial and temporal resolution through the use of a short-range Lidar WindScanner, within the wind tunnel of ForWind-Oldenburg. This technique provides the opportunity to analyse the flow structures at different operational and inflow conditions in a relative fast manner without disturbing the flow. Experiments were conducted using a model wind turbine in a large cross-section wind tunnel. The short-range Lidar WindScanner is used as the primary instrument to map the wind turbine wake at different downstream locations. The flow structures of the wake were measured from 1 D up to 10 D downstream of the turbine rotor. A stable flow within the wind tunnel segment is measured, which is crucial for the analyses of the evolution of the wake. In addition, a high detailed spatial resolution of the wake profile is observed, showing the symmetric and asymmetric behaviour of the wake, for unyawed and yawed conditions, respectively. Furthermore, the calculation of the thrust coefficient from the velocity data show expected behaviour, giving further credibility to the measurement technique.
  • Authors

  • Hulsman, Paul
  • Wosnik, Martin
  • Petrovic, Vlaho
  • Hoelling, Michael
  • Kuehn, Martin
  • IOP
  • Status

    Publication Date

  • 2020
  • Digital Object Identifier (doi)

    Start Page

  • 012007
  • End Page

  • 012007
  • Volume

  • 1452
  • Issue

  • 1