用新方法提升电力系统电压控制的计算与采样效率
Digital Twin-Empowered Voltage Control for Power Systems
- 引入Gumbel策略优化，减少对蒙特卡洛搜索的依赖
- 通过一致性损失函数提升隐状态预测准确率
- 在多个测试系统上实测效率优于现有技术
新兴的数字孪生技术有望革新电力系统的电压控制。然而，当前最先进的数字孪生方法存在计算和采样效率低的问题，限制了其应用。为此，本文提出一种基于Gumbel一致性的数字孪生（GC-DT）方法，以提升电压控制的效率。首先，采用基于Gumbel的策略改进方法，利用Gumbel-top技巧增强非重复采样动作，降低对蒙特卡洛树搜索模拟的依赖，从而提高计算效率。其次，设计一致性损失函数，使预测的隐状态与真实隐状态在潜在空间中对齐，进一步提升预测精度和采样效率。在IEEE 123-bus、34-bus和13-bus系统上的实验表明，所提GC-DT方法在计算和采样效率方面均优于当前最优数字孪生方法。
原文摘要 · Abstract (English)
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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