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Digital Twin-Empowered Voltage Control for Power Systems

arXiv 2412.06940 ↗First posted 9 Dec 2024cs.LG eess.SPcited by 0

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Abstract (arXiv)

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.

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References · 3

  1. 2021Mastering Atari Games with Limited Datacited by 237
  2. 2020Deep Reinforcement Learning Based Volt-VAR Optimization in Smart Distribution Systemscited by 17
  3. 2021PowerGym: A Reinforcement Learning Environment for Volt-Var Control in Power Distribution Systemscited by 14

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