Dynamic Modeling of Cascading Failure in Power Systems

TL;DR

This paper introduces a dynamic simulation model for power system cascading failures that captures more mechanisms than traditional models, allowing better analysis of blackout risks and interactions.

Contribution

The work presents a comprehensive dynamic model of power systems and protections, enabling simulation of diverse cascading outage mechanisms beyond quasi-steady state models.

Findings

The dynamic model's results correlate well with historical blackout data.

Load models significantly influence cascading failure risks.

The dynamic and QSS models largely agree but differ in later cascade stages.

Abstract

The modeling of cascading failure in power systems is difficult because of the many different mechanisms involved; no single model captures all of these mechanisms. Understanding the relative importance of these different mechanisms is an important step in choosing which mechanisms need to be modeled for particular types of cascading failure analysis. This work presents a dynamic simulation model of both power networks and protection systems, which can simulate a wider variety of cascading outage mechanisms, relative to existing quasi-steady state (QSS) models. The model allows one to test the impact of different load models and protections on cascading outage sizes. This paper describes each module of the developed dynamic model and demonstrates how different mechanisms interact. In order to test the model we simulated a batch of randomly selected $N-2$ contingencies for several different static load configurations, and found that the distribution of blackout sizes and event lengths from the proposed dynamic simulator correlates well with historical trends. The results also show that load models have significant impacts on the cascading risks. This dynamic model was also compared against a QSS model based on the dc power flow approximations; we find that the two models largely agree, but produce substantially different results for later stages of cascading.