Spatio-Temporal Failure Propagation in Cyber-Physical Power Systems

TL;DR

This paper introduces an asynchronous algorithm to analyze how failures propagate over space and time in cyber-physical power systems, considering complex nonlinear physics and operational constraints.

Contribution

It presents a novel asynchronous method for modeling failure spread in CPPS using full AC power flow equations and practical operational constraints.

Findings

Failure propagation patterns depend on attack size and location

The approach effectively visualizes cascading failure evolution

Insights aid in preventive system design and operation

Abstract

Cascading failure in power systems is triggered by a small perturbation that leads to a sequence of failures spread through the system. The interconnection between different components in a power system causes failures to easily propagate across the system. The situation gets worse by considering the interconnection between cyber and physical layers in power systems. A plethora of work has studied the cascading failure in power systems to calculate its impact on the system. Understanding how failures propagate into the system in time and space can help the system operator to take preventive actions and upgrade the system accordingly. Due to the nonlinearity of the power flow equation as well as the engineering constraints in the power system, it is essential to understand the spatio-temporal failure propagation in cyber-physical power systems (CPPS). This paper proposes an asynchronous algorithm for investigating failure propagation in CPPS. The physics of the power system is addressed by the full AC power flow equations. Various practical constraints including load shedding, load-generation balance, and island operation are considered to address practical constraints in power system operation. The propagation of various random initial attacks of different sizes is analyzed and visualized to elaborate on the applicability of the proposed approach. Our findings shed light on the cascading failure evolution in CPPS.