An Interaction Model for Simulation and Mitigation of Cascading Failures
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Abstract (arXiv)
In this paper the interactions between component failures are quantified and the interaction matrix and interaction network are obtained. The quantified interactions can capture the general propagation patterns of the cascades from utilities or simulation, thus helping to better understand how cascading failures propagate and to identify key links and key components that are crucial for cascading failure propagation. By utilizing these interactions a high-level probabilistic model called interaction model is proposed to study the influence of interactions on cascading failure risk and to support online decision-making. It is much more time efficient to first quantify the interactions between component failures with fewer original cascades from a more detailed cascading failure model and then perform the interaction model simulation than it is to directly simulate a large number of cascades with a more detailed model. Interaction-based mitigation measures are suggested to mitigate cascading failure risk by weakening key links, which can be achieved in real systems by wide area protection such as blocking of some specific protective relays. The proposed interaction quantifying method and interaction model are validated with line outage data generated by the AC OPA cascading simulations on the IEEE 118-bus system.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Jan 2014.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 3; 2025: 2.
6 papers.
- 2024Cascading Failure Prediction via Causal Inferencecited by 3
- 2024Cascading Blackout Severity Prediction with Statistically-Augmented Graph Neural Networkscited by 2
- 2021Power Grid Cascading Failure Mitigation by Reinforcement Learningcited by 1
- 2024A Dual Power Grid Cascading Failure Model for the Vulnerability Analysiscited by 1
- 2025Real-Time Risky Fault-Chain Search using Time-Varying Graph RNNscited by 0
- 2025Real-Time Cascade Mitigation in Power Systems Using Influence Graph Improved by Reinforcement Learningcited by 0
- 2025Real-Time Cascade Mitigation in Power Systems Using Influence Graph Improved by Reinforcement Learning10 Jun 2025
- 2025Real-Time Risky Fault-Chain Search using Time-Varying Graph RNNs12 Mar 2025
- 2024Cascading Failure Prediction via Causal Inference24 Oct 2024
- 2024A Dual Power Grid Cascading Failure Model for the Vulnerability Analysis18 May 2024
- 2024Cascading Blackout Severity Prediction with Statistically-Augmented Graph Neural Networks22 Mar 2024
- 2021Power Grid Cascading Failure Mitigation by Reinforcement Learning23 Aug 2021