Content area

Abstract

Cybersecurity is one of the most difficult challenges posed by the revolutionary smart power system. Cyberattacks on power grids have already caused widespread, temporary outages via Phasor Measurement Unit (PMUs). When a PMU is hacked with a false data injection attack, it can lead to unexpected errors in state estimate variables such as buses voltage, buses angles and their magnitudes then cascade failures. Previous studies suggest deploying PMU is to operate secure Generation and Transmission lines on the power system utilizing a variety of approaches and strategies to maintain voltage stability or improve power transfer. This study utilized the Observability Redundancy to deploy PMUs at optimal locations along a network to ensure the grid's critical observability to eliminate false data injection vulnerability. The fundamental objective of this initiative is to strategically deploy PMUs to minimize the grid's susceptibility to a potential fake data injection cyberattack and to increase grid observability redundancy through a limited number of PMUs and use historical data for current data validation. Using the MATLAB platform, the results are compared to demonstrate the system's enhancement. On the IEEE 30 bus test system, the suggested scheme's usefulness has been proven through effective testing.

Details

1010268
Title
Impact of False Data Injection Attack in Power Systems and a Proposed Method to Mitigate Risk
Author
Number of pages
102
Publication year
2025
Degree date
2025
School code
0755
Source
DAI-B 86/12(E), Dissertation Abstracts International
ISBN
9798280703261
Committee member
Nyarko, Kofi; Mcghee-Bey, Parris
University/institution
Morgan State University
Department
Electrical and Computer Engineering
University location
United States -- Maryland
Degree
Ph.D.
Source type
Dissertation or Thesis
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
31843702
ProQuest document ID
3215717370
Document URL
https://www.proquest.com/dissertations-theses/impact-false-data-injection-attack-power-systems/docview/3215717370/se-2?accountid=208611
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Database
ProQuest One Academic