Detection of cyber attack in smart grid: A Comparative Study

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1 Citation (Scopus)
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Abstract

Smart grid steady control relies heavily on the communication infrastructure among sensors, actuators, and control systems, which makes it vulnerable to cyber-attacks. Accurate acquisition of dynamic state information is deemed vital for efficient detection of these cyber-attacks on a smart grid. However, several popular state estimation methods at the present stage are restricted in practical use and require some assumptions. In this paper, we investigate the security of smart grid systems. We (1) identify and define the security problem in the smart grid, (2) compare the performance of several state estimate methods including Least Square, Kalman filter, Extend Kalman filter, in identifying smart grid dynamic information using measurements, and (3) investigate the Chi-square detector, Euclidean Distance, and Cosine similarity matching approaches for attack detection.

Original languageEnglish
Title of host publication2022 IEEE 20th International Power Electronics and Motion Control Conference, PEMC 2022
PublisherIEEE
Pages48-54
Number of pages7
ISBN (Electronic)9781665496810
DOIs
Publication statusPublished - 2022
Event20th IEEE International Power Electronics and Motion Control Conference, PEMC 2022 - Brasov, Romania
Duration: 25 Sept 202228 Sept 2022

Publication series

Name2022 IEEE 20th International Power Electronics and Motion Control Conference, PEMC 2022

Conference

Conference20th IEEE International Power Electronics and Motion Control Conference, PEMC 2022
Country/TerritoryRomania
CityBrasov
Period25/09/2228/09/22

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Cyber attack detection
  • Kalman filter
  • smart grid
  • State estimate

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