Detection of false data injection attacks on wide-area under-frequency load shedding protection schemes

Mohsen Khalaf, Amr Youssef, Ehab F. El-Saadany, Magdy Salama

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we first investigate the problem of cyber attacks on Wide-Area Protection (WAP) schemes. As a case for study, false data injection (FDI) attacks on wide-area Under-Frequency Load Shedding (UFLS) protection schemes are considered. Our analysis shows that attackers can drive the system out of stability by manipulating frequency measurements that are supplied to the control center by each local system. Then, we propose a detection strategy based on an unknown input estimator using Kalman filter, where frequencies as well as the power disturbance of system generators are estimated and compared with the received values. Then, a decision is made whether there is an attack or not based on the cumulative error residual. The effectiveness of the proposed approach in detecting FDI on wide-area UFLS protection schemes is confirmed through simulation using the IEEE 14 bus benchmark system.

Original languageBritish English
Title of host publication2019 IEEE Electrical Power and Energy Conference, EPEC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728134062
DOIs
StatePublished - Oct 2019
Event2019 IEEE Electrical Power and Energy Conference, EPEC 2019 - Montreal, Canada
Duration: 16 Oct 201918 Oct 2019

Publication series

Name2019 IEEE Electrical Power and Energy Conference, EPEC 2019

Conference

Conference2019 IEEE Electrical Power and Energy Conference, EPEC 2019
Country/TerritoryCanada
CityMontreal
Period16/10/1918/10/19

Keywords

  • False Data Injection
  • Kalman Filter
  • Unknown Input Estimator
  • Wide-Area Protection

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