Status: this preprint has been withdrawn by the authors.
Unlocking the Full Potential of Wake Steering: Implementation and Assessment of a Controls-Oriented Model
Christopher J. Bay,Jennifer King,Paul Fleming,Rafael Mudafort,and Luis A. MartÃnez-Tossas
Abstract. In this work, a controls-oriented wake model is modified and compared to an analytical Gaussian wake model and high-fidelity simulation data. This model, called the curled wake model, captures a wake phenomenon that occurs behind yawed turbines, modeled as a collection of vortices shed from the rotor plane. Through turbine simulations, these vortices are shown to have a significant impact on the prediction of wake steering's performance. Also, optimizations using the model are performed and produce results consistent with recent published research. Results indicate that wind farm controllers designed and analyzed with the curled wake model produce wake steering controllers which can realize larger gains in power production than previously estimated. Overall, the results support the concept of secondary steering, or a yawed turbine's ability to deflect the wake of a downstream turbine, and suggest that future turbine wake studies and yaw optimizations should include the curled wake phenomenon.
This preprint has been withdrawn.
Received: 25 Apr 2019 – Discussion started: 07 May 2019
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This work details a new low-fidelity wake model to be used in determining operational strategies for wind turbines. With the additional physics that this model captures, optimizations have found new control strategies that provide greater increases in performance than previously determined, and these performance increases have been confirmed in high-fidelity simulations. As such, this model can be used in the design and optimization of future wind farms and operational schemes.
This work details a new low-fidelity wake model to be used in determining operational strategies...
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