Self-Learning Data-Driven Wind Farm Control Strategy Using Field Measurements-Reference-Cited by-同舟云学术

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Self-Learning Data-Driven Wind Farm Control Strategy Using Field Measurements

Published:2024-07-10 Issue: Volume: Page:1057-1064
ISSN:
Container-title:2024 American Control Conference (ACC)
language:
Short-container-title:

Author:

Hulsman P.¹,Howland M.²,Göçmen T.³,Petrović V.¹,Kühn M.¹

Affiliation:

1. Carl von Ossietzky Universität Oldenburg, Institute of Physics,ForWind - Center for Wind Energy Research,Oldenburg,Germany

2. Massachusetts Institute of Technology,Civil and Environmental Engineering,Cambridge,USA

3. Technical University of Denmark,DTU Wind Energy,Lyngby,Denmark

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10644130/10644150/10644839.pdf?arnumber=10644839

Reference23 articles.

1. Expert Elicitation on Wind Farm Control

2. Simulation comparison of wake mitigation control strategies for a two-turbine case

3. Estimating the wake deflection downstream of a wind turbine in different atmospheric stabilities: an LES study

4. Wind tunnel study on power output and yaw moments for two yaw-controlled model wind turbines

5. Development of a curled wake of a yawed wind turbine under turbulent and sheared inflow

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