Deep Reinforcement Learning for Automatic Generation Control of Wind Farms-Reference-Cited by-同舟云学术

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Deep Reinforcement Learning for Automatic Generation Control of Wind Farms

Published:2021-05-25 Issue: Volume: Page:
ISSN:
Container-title:2021 American Control Conference (ACC)
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Author:

Vijayshankar Sanjana,Stanfel Paul,King Jennifer,Spyrou Evangelia,Johnson Kathryn

Funder

National Renewable Energy Laboratory

Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9482409/9482614/09483277.pdf?arnumber=9483277

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Review on the Application of Artificial Intelligence Methods in the Control and Design of Offshore Wind Power Systems;Journal of Marine Science and Engineering;2024-02-27

2. Data-Driven Approach for Wind Farm Control: Toward an Alternative to FLORIS;IEEE Access;2024

3. Digital Transformation and AI in Energy Systems: Applications, Challenges, and the Path Forward;Palgrave Studies in Digital Business & Enabling Technologies;2024

4. Reinforcement Learning-Based Wind Farm Control: Toward Large Farm Applications via Automatic Grouping and Transfer Learning;IEEE Transactions on Industrial Informatics;2023-12

5. Reinforcement learning in wind energy - a review;International Journal of Green Energy;2023-11-15

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