The Texas power grid on the Gulf Coast of the United States is frequently hit by tropical cyclones (TCs) causing widespread power outages, a risk that is expected to substantially increase under global warming. Here we introduce a new approach that combines a probabilistic line failure model with a network model of the Texas grid to simulate the spatio-temporal co-evolution of wind-induced failures of high-voltage transmission lines and the resulting cascading power outages from seven major historical TCs. The approach allows reproducing observed supply failures. In addition, compared to existing static approaches, it provides a notable advantage in identifying critical lines whose failure can trigger large supply shortages. We show that hardening only 1% of total lines can reduce the likelihood of the most destructive type of outage by a factor of between 5 and 20. The proposed modelling approach could represent a so far missing tool for identifying effective options to strengthen power grids against future TC strikes, even under limited knowledge.

美国墨西哥湾沿岸的德克萨斯州电网经常受到热带气旋（TC）的袭击，导致大范围停电，预计在全球变暖的情况下，这一风险将大幅增加。在这里，我们介绍一种新方法，将概率线路故障模型与德克萨斯州电网的网络模型相结合，模拟高压输电线路风致故障的时空协同演化以及由此导致的七个主要电网的级联停电。历史 TC。该方法允许重现观察到的电源故障。此外，与现有的静态方法相比，它在识别故障可能引发严重供应短缺的关键线路方面具有显着优势。我们表明，仅加固总线路的 1% 就可以将最具破坏性的停电类型的可能性降低 5 到 20 倍。所提出的建模方法可以代表迄今为止缺少的工具，用于识别加强电网的有效选项。即使在知识有限的情况下，未来的 TC 也会罢工。