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Deep Synchronization Control of Grid-Forming Converters: A Reinforcement Learning Approach

  • Xi'an Jiaotong University
  • University of Victoria BC

科研成果: 期刊稿件 › 文章 › 同行评审

9 引用 (Scopus)

摘要

Dear Editor, This letter proposes a deep synchronization control (DSC) method to synchronize grid-forming converters with power grids. The method involves constructing a novel controller for grid-forming converters based on the stable deep dynamics model. To enhance the performance of the controller, the dynamics model is optimized within the deep reinforcement learning (DRL) framework. Simulation results verify that the proposed method can reduce frequency deviation and improve active power responses.

源语言英语
页(从-至)273-275
页数3
期刊IEEE/CAA Journal of Automatica Sinica
卷12
期1
DOI
出版状态已出版 - 2025

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