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Digital Twin-Empowered Voltage Control for Power Systems

Machine Learning 2024-12-11 v1 Signal Processing

Abstract

Emerging digital twin technology has the potential to revolutionize voltage control in power systems. However, the state-of-the-art digital twin method suffers from low computational and sampling efficiency, which hinders its applications. To address this issue, we propose a Gumbel-Consistency Digital Twin (GC-DT) method that enhances voltage control with improved computational and sampling efficiency. First, the proposed method incorporates a Gumbel-based strategy improvement that leverages the Gumbel-top trick to enhance non-repetitive sampling actions and reduce the reliance on Monte Carlo Tree Search simulations, thereby improving computational efficiency. Second, a consistency loss function aligns predicted hidden states with actual hidden states in the latent space, which increases both prediction accuracy and sampling efficiency. Experiments on IEEE 123-bus, 34-bus, and 13-bus systems demonstrate that the proposed GC-DT outperforms the state-of-the-art DT method in both computational and sampling efficiency.

Keywords

Cite

@article{arxiv.2412.06940,
  title  = {Digital Twin-Empowered Voltage Control for Power Systems},
  author = {Jiachen Xu and Yushuai Li and Torben Bach Pedersen and Yuqiang He and Kim Guldstrand Larsen and Tianyi Li},
  journal= {arXiv preprint arXiv:2412.06940},
  year   = {2024}
}

Comments

6 pages, 1 figure, conference paper

R2 v1 2026-06-28T20:28:35.830Z