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Reinforcement Learning Based Weighting Factors’ Real-Time Updating Scheme for the FCS Model Predictive Control to Improve the Large-Signal Stability of Inverters

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Stability Enhancement Methods of Inverters Based on Lyapunov Function, Predictive Control, and Reinforcement Learning

Abstract

The previous chapter demonstrates that the finite control set (FCS) model predictive control.

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Author information

Authors and Affiliations

  1. College of Electrical Engineering, Zhejiang University, Hangzhou, Zhejiang, China

    Xin Zhang

  2. Power Dispatching and Control Center of China Southern Power Grid, Guangzhou, Guangdong, China

    Jinsong He

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Jinsong He

  4. College of Electrical Engineering, Zhejiang University, Hangzhou, Zhejiang, China

    Hao Ma & Xiaohai Ge

  5. National Maglev Transportation Engineering R&D Center, Tongji University, Shanghai, China

    Zhixun Ma

Authors
  1. Xin Zhang
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  2. Jinsong He
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  3. Hao Ma
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  4. Zhixun Ma
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  5. Xiaohai Ge
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Corresponding author

Correspondence to Xin Zhang .

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Zhang, X., He, J., Ma, H., Ma, Z., Ge, X. (2023). Reinforcement Learning Based Weighting Factors’ Real-Time Updating Scheme for the FCS Model Predictive Control to Improve the Large-Signal Stability of Inverters. In: Stability Enhancement Methods of Inverters Based on Lyapunov Function, Predictive Control, and Reinforcement Learning. Springer, Singapore. https://doi.org/10.1007/978-981-19-7191-4_8

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  • DOI: https://doi.org/10.1007/978-981-19-7191-4_8

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-7190-7

  • Online ISBN: 978-981-19-7191-4

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