Parameter tuning of new type energy virtual synchronous generator based on physics-informed reinforcement learning-Reference-Cited by-同舟云学术

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Parameter tuning of new type energy virtual synchronous generator based on physics-informed reinforcement learning

Published:2023-09-22 Issue: Volume: Page:
ISSN:
Container-title:2023 8th International Conference on Power and Renewable Energy (ICPRE)
language:
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Author:

Qiu Jian¹,Yang Huanhuan¹,Zhang Jianxin¹,Gao Jiemai²,Jiang Tuo¹,Gao Qin¹,Chen Junquan³,Xu Guanghu¹

Affiliation:

1. China Southern Power Grid Co., Ltd.,Electric Power Dispatching and Control Center,Guangzhou,China

2. Wuhan University,School of Electrical Engineering and Automation,Wuhan,China

3. CSG Guizhou Power Grid Corporation,Electric Power Dispatching and Control Center,Guizhou,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10353070/10353550/10353614.pdf?arnumber=10353614

Reference22 articles.

1. On the Stability of Power Electronics-Dominated Systems: Challenges and Potential Solutions

2. On the Stability of the Power Electronics-Dominated Grid: A New Energy Paradigm

3. System impact studies for near 100% renewable energy systems dominated by inverter based variable generation

4. Practical Framework for Frequency Stability Studies in Power Systems With Renewable Energy Sources

Cited by 1 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. Deep and Reinforcement Learning in Virtual Synchronous Generator: A Comprehensive Review;Energies;2024-05-29

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