论文标题
揭示了HVDC跨区域流与频率稳定性与可解释AI之间的相互作用
Revealing interactions between HVDC cross-area flows and frequency stability with explainable AI
论文作者
论文摘要
能量转换将更多挥发性的能源引入功率网格中。在这种情况下，通过高压直流电（HVDC）链接之间的不同同步区域之间的功率传递变得越来越重要。这样的链接可以通过启用长途运输或利用其快速控制行为来平衡挥发性的产生。在这里，我们研究了功率失衡的相互作用 - 通过电网频率表示 - 以及欧洲同步区域之间HVDC链路上的功率流。我们使用可解释的机器学习来识别关键依赖性并解开关键特征的相互作用。我们的结果表明，基于市场的HVDC流引入确定性频率偏差，但是可以通过严格的渐升限制来减轻这些偏差。此外，不同的HVDC操作模式强烈影响与网格的相互作用。特别是，我们表明，通过HVDC链接进行负载频率控制可以对频率稳定性产生类似控制或干扰的影响。
The energy transition introduces more volatile energy sources into the power grids. In this context, power transfer between different synchronous areas through High Voltage Direct Current (HVDC) links becomes increasingly important. Such links can balance volatile generation by enabling long-distance transport or by leveraging their fast control behavior. Here, we investigate the interaction of power imbalances - represented through the power grid frequency - and power flows on HVDC links between synchronous areas in Europe. We use explainable machine learning to identify key dependencies and disentangle the interaction of critical features. Our results show that market-based HVDC flows introduce deterministic frequency deviations, which however can be mitigated through strict ramping limits. Moreover, varying HVDC operation modes strongly affect the interaction with the grid. In particular, we show that load-frequency control via HVDC links can both have control-like or disturbance-like impacts on frequency stability.
