Dynamically induced cascading failures in power grids

TL;DR

This paper introduces a dynamic framework for modeling cascading failures in power grids, emphasizing transient behaviors and proposing a forecasting method to identify critical components, enhancing understanding and prediction of large-scale outages.

Contribution

It presents a novel dynamic modeling approach that incorporates transient behaviors and offers a forecasting method for critical line identification in power grids.

Findings

Transient dynamics are crucial for cascade emergence.

The framework improves prediction of critical components.

Dynamic failures significantly affect grid synchronization.

Abstract

Reliable functioning of infrastructure networks is essential for our modern society. Cascading failures are the cause of most large-scale network outages. Although cascading failures often exhibit dynamical transients, the modeling of cascades has so far mainly focused on the analysis of sequences of steady states. In this article, we focus on electrical transmission networks and introduce a framework that takes into account both the event-based nature of cascades and the essentials of the network dynamics. We find that transients of the order of seconds in the flows of a power grid play a crucial role in the emergence of collective behaviors. We finally propose a forecasting method to identify critical lines and components in advance or during operation. Overall, our work highlights the relevance of dynamically induced failures on the synchronization dynamics of national power grids of different European countries and provides methods to predict and model cascading failures.