Data-driven Optimal Control Strategy for Virtual Synchronous Generator via Deep Reinforcement Learning Approach

Data-driven Optimal Control Strategy for Virtual Synchronous Generator via Deep Reinforcement Learning Approach

This paper aims at developing a data-driven optimal control strategy for virtual synchronous generator (VSG) in the scenario where no expert knowledge or requirement for system model is available. Firstly, the optimal and adaptive control problem for VSG is transformed into a reinforcement learning...

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Bibliographic Details
Main Authors: Yushuai Li, Wei Gao, Shuo Huang, Rui Wang, Weihang Yan, Vahan Gevorgian, David Wenzhong Gao
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:Journal of Modern Power Systems and Clean Energy
Subjects:
Adaptive control
virtual synchronous generator (VSG)
reinforcement learning
deep learning
Online Access:https://ieeexplore.ieee.org/document/9335702/

Internet

https://ieeexplore.ieee.org/document/9335702/

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