Analyzing the Impact of AC False Data Injection Attacks on Power System Operation

TL;DR

This paper investigates the impact of AC false data injection attacks on power systems, highlighting how optimally designed attacks can evade detection and cause varying degrees of system disruption.

Contribution

It presents a unified approach to analyze AC FDI attack impacts, comparing optimal and arbitrary attack designs using PowerWorld on the IEEE 39-bus system.

Findings

Optimal AC FDI attacks cause fewer state changes and residuals.

Impact severity varies between optimal and arbitrary attacks.

Trade-offs exist between attack residuals and system impact.

Abstract

False Data Injection (FDI) attacks are a significant threat to modern power systems. Although numerous research studies have focused on FDI attacks on power systems, these studies have primarily concentrated on designing or detecting DC FDI attacks, with less attention given to the impact analysis of AC FDI attacks. AC FDI attacks are potentially more harmful as they can easily bypass bad data detection (BDD) algorithms. In this paper, we present a unified approach to investigate the impact of AC FDI attacks on power transmission lines using the PowerWorld simulator. We also investigate the impact of different FDI attack designs, including those optimally designed to evade BDD algorithms and compare them accordingly. Our findings demonstrate that in designing optimal AC FDI attacks, a trade-off between the residuals of state variables and the corresponding impacts of the proposed attack should be considered. This is because optimal attacks result in fewer changes in the attacked variable states and their estimated residuals compared to arbitrary AC FDI attacks. Moreover, the impacts of optimal AC FDI attacks can be less severe than those of arbitrary attacks. We implement and analyze the proposed approach on the IEEE 39-bus test system using PowerWorld simulator.