Interaction Graphs for Cascading Failure Analysis in Power Grids: A Survey

TL;DR

This survey reviews various data-driven and physics-based graph models used to analyze cascading failures in power grids, highlighting their role in understanding complex component interactions and improving system reliability.

Contribution

It provides a comprehensive overview of methods for constructing interaction graphs and their application in cascading failure analysis in power grids.

Findings

Interaction graphs help reveal complex component dependencies.

Graph-based models improve understanding of failure propagation.

Various techniques have been developed for interaction graph construction.

Abstract

Understanding and analyzing cascading failures in power grids have been the focus of many researchers for years. However, the complex interactions among the large number of components in these systems and their contributions to cascading failures are not yet completely understood. Therefore, various techniques have been developed and used to model and analyze the underlying interactions among the components of the power grid with respect to cascading failures. Such methods are important to reveal the essential information that may not be readily available from power system physical models and topologies. In general, the influences and interactions among the components of the system may occur both locally and at distance due to the physics of electricity governing the power flow dynamics as well as other functional and cyber dependencies among the components of the system. To infer and capture such interactions, data-driven approaches or techniques based on the physics of electricity have been used to develop graph-based models of interactions among the components of the power grid. In this survey, various methods of developing interaction graphs as well as studies on the reliability and cascading failure analysis of power grids using these graphs have been reviewed.