data for "Dynamic risk assessment of wildfire-induced transmission line breakdown based on data assimilation method"

Wildfires represent an escalating threat to critical infrastructure, particularly transmission lines, leading to severe power outages and significant economic repercussions. This study addresses the urgent need for effective risk assessment methods in the face of rapidly evolving wildfire dynamics. By leveraging data assimilation techniques, a novel dynamic risk assessment framework is proposed, utilizing a real-world wildfire case study. Observational data is seamlessly integrated into traditional wildfire propagation simulations through an ensemble transform Kalman filter, enhancing predictive accuracy of fire line positions and their associated uncertainties. The use of multi-parameter updates further refines the data assimilation process, avoiding the limitations of only updating the position of the fire line or updating a single parameter of a certain type. Additionally, a Monte Carlo simulation-based approach is developed to dynamically calculate the probability of wildfire arrival, coupled with a robust quantitative method for assessing the likelihood of transmission line failures under extreme fire scenarios. The fire line intensity, determined under the worst-case scenario principle, serves as the input for the quantitative assessment framework. By synthesizing wildfire arrival and transmission line failure probabilities, this research offers a comprehensive real-time risk assessment tool, thereby providing a fresh perspective on managing the interface between wildfires and critical infrastructure.

野火对关键基础设施构成日益严峻的威胁，尤以输电线路为甚，可引发严重停电与显著的经济负面效应。本研究针对野火动态快速演变场景下高效风险评估方法的迫切需求展开工作。借助数据同化（data assimilation）技术，结合真实野火案例研究，本研究提出了一种全新的动态风险评估框架：通过集合变换卡尔曼滤波器（ensemble transform Kalman filter），将观测数据无缝融入传统野火蔓延模拟流程，有效提升了火线位置及其相关不确定性的预测精度。采用多参数更新策略进一步优化了数据同化流程，规避了仅更新火线位置或仅更新某类单一参数的局限性。此外，本研究开发了基于蒙特卡洛模拟（Monte Carlo simulation）的动态计算方法，用以求解野火抵达目标区域的概率；同时配套构建了一套稳健的定量评估方法，用于评估极端火情场景下输电线路的故障概率。基于最坏场景原则确定的火线强度，将作为该定量评估框架的输入参数。本研究通过整合野火抵达概率与输电线路故障概率，形成了一套完整的实时风险评估工具，为野火与关键基础设施的交互界面管理提供了全新的研究视角。