Cascading failures in power networks pose a significant threat, capable of escalating from isolated line outages to extensive blackouts with severe economic and societal impacts. The topic presents a probabilistic framework designed to assess and compute the risk of cascading failures within the power network and rank various cascade contingencies, utilizing the IEEE39 bus 10-machine New England Power System. Using DigSILENT PowerFactory, a detailed contingency analysis was conducted, focusing on line loading conditions following faults as a starting point. This approach operates under the foundational assumption that cascading failures can be effectively modelled through the sequential analysis of line contingencies. Central to this framework is assessing topological vulnerabilities in the grid and determining frequently occurring outage patterns called probabilistic contingency motifs (PCMs). By analyzing the characteristics of the grid, an impact metric is proposed using short-circuit analysis, electrical distance and LODFs for the identified cascade contingency. The outage probabilities and the proposed impacts are used to compute the risks of cascade cases.

After ranking based on their associated risks, high-risk contingencies are dynamically simulated through time-domain simulations to assess dynamic security. This simulation approach validates the model's predictions and ensures that ranked contingencies reflect realistic cascades. Use cases can show that the model will enable Transmission System Operators (TSOs) to implement preventive measures and simulate corrective actions effectively. By systematically identifying and incorporating PCMs and leveraging grid topology, the model estimates the likelihood and impact of cascading events and delivers actionable insights for improving power system robustness. Future work will expand the framework’s scalability to larger and more complex networks and integrate real-time data streams to facilitate dynamic risk assessment and proactive mitigation strategies.