Evaluating power system vulnerability to false data injection attacks via scalable optimization

Zhigang Chu, Jiazi Zhang, Oliver Kosut, Lalitha Sankar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

Physical consequences to power systems of false data injection cyber-attacks are considered. Prior work has shown that the worst-case consequences of such an attack can be determined using a bi-level optimization problem, wherein an attack is chosen to maximize the physical power flow on a target line subsequent to re-dispatch. This problem can be solved as a mixed-integer linear program, but it is difficult to scale to large systems due to numerical challenges. Three new computationally efficient algorithms to solve this problem are presented. These algorithms provide lower and upper bounds on the system vulnerability measured as the maximum power flow subsequent to an attack. Using these techniques, vulnerability assessments are conducted for IEEE 118-bus system and Polish system with 2383 buses.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Smart Grid Communications, SmartGridComm 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages260-265
Number of pages6
ISBN (Electronic)9781509040759
DOIs
StatePublished - Dec 8 2016
Event7th IEEE International Conference on Smart Grid Communications, SmartGridComm 2016 - Sydney, Australia
Duration: Nov 6 2016Nov 9 2016

Other

Other7th IEEE International Conference on Smart Grid Communications, SmartGridComm 2016
CountryAustralia
CitySydney
Period11/6/1611/9/16

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Control and Optimization
  • Signal Processing

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