Efficient Optimization of Large Wind Farms for Real-Time Control: Preprint

Paul Fleming, Kathryn Johnson, Christopher Bay, Timothy Taylor, Lucy Pao

Research output: Contribution to conferencePaper

Abstract

Wind turbines in a wind farm typically operate individually to maximize their own performance regardless of the impact of aerodynamic interactions on neighboring turbines. Properly coordinating turbines, by operating some turbines suboptimally, within a wind farm has the potential to improve overall wind farm performance. Computing the optimal control strategy under varying atmospheric conditions can be computationally intense for large wind farms. As wind power farms increase in size and related models become more complex, computationally efficient algorithms are needed to perform real-time optimization and control. This study proposes a distributed optimization framework and computationally efficient wake steering wind farm control strategy that uses the yaw angle of a turbine to alter the behavior of a turbine wake and minimize turbine interactions. This computational efficiency allows the strategy to be feasible for real-time control.
Original languageAmerican English
Number of pages8
StatePublished - 2018
EventAmerican Control Conference - Milwaukee, Wisconsin
Duration: 27 Jun 201829 Jun 2018

Conference

ConferenceAmerican Control Conference
CityMilwaukee, Wisconsin
Period27/06/1829/06/18

Bibliographical note

See NREL/CP-5000-73416 for paper as published in IEEE proceedings

NREL Publication Number

  • NREL/CP-5000-70937

Keywords

  • distributed optimization
  • real time
  • wind energy
  • wind farm control

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