Flow Control Leveraging Downwind Rotors for Improved Wind Power Plant Operation

Research output: Contribution to conferencePaperpeer-review

16 Scopus Citations

Abstract

Controlling the air flow within wind power plants has the potential to improve plant performance and is an active area of research in the wind energy control community. In order to develop, test, and tune wind power plant controllers efficiently, an accurate engineering model of the turbine wake dynamics is required. Two elements of flow control are wake steering via yaw and tilt of a turbine. When a turbine is yawed or tilted away from the incoming wind field, the wake shape is changed. This is largely due to shed vortices that produce a curled wake. In this work, the well-known wake engineering model FLOw Redirection and Induction in Steady State (FLORIS) wake engineering model is enhanced to include these curled wake effects due to tilt. Since decay of these vortices has not been previously captured in an engineering model, the authors describe how vortices with decay have been added to FLORIS and how the updated model has been used to study the effects due to tilt in the wake. Results are demonstrated and compared to high-fidelity large-eddy simulations. Potential wind power plant performance gains due to flow control using tilt are investigated across different wind conditions and sites. Preliminary results show power gains by using tilt to implement flow control in a variety of wind distributions and tilt values.

Original languageAmerican English
Pages2843-2848
Number of pages6
DOIs
StatePublished - Jul 2019
Event2019 American Control Conference, ACC 2019 - Philadelphia, United States
Duration: 10 Jul 201912 Jul 2019

Conference

Conference2019 American Control Conference, ACC 2019
Country/TerritoryUnited States
CityPhiladelphia
Period10/07/1912/07/19

Bibliographical note

See NREL/CP-5000-73125 for preprint

NREL Publication Number

  • NREL/CP-5000-75052

Keywords

  • FLORIS
  • flow control
  • performance
  • wind energy
  • wind farm

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