Skip to main navigation Skip to search Skip to main content

Detection of False Data Injection and Series Arc Faults in DC Microgrids Based on Unknown Input Observers

  • SUNY Buffalo

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

5 Scopus citations

Abstract

DC microgrid's secondary control consists of physical and cyber layers with cooperative control structure that relies on the communication between different subsystems. This makes the system vulnerable to cyber attacks that can disrupt the system stability. Meanwhile, physical faults, such as series arc fault, can also cause significant threat to the stability and operation of the system. In this paper, an architecture to detect both false data injection and series arc faults for DC microgrids with distributed generation units (DGU) is proposed. Two types of unknown input observers (UIO) are used to achieve the detection and identification. The proposed UIOs are verified through hardware in the loop simulations.

Original languageEnglish
Title of host publication2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1155-1159
Number of pages5
ISBN (Electronic)9798350316445
DOIs
StatePublished - 2023
Event2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023 - Nashville, United States
Duration: Oct 29 2023Nov 2 2023

Publication series

Name2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

Conference

Conference2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023
Country/TerritoryUnited States
CityNashville
Period10/29/2311/2/23

Keywords

  • Arc fault
  • Cyber attack
  • Detection
  • Microgrids
  • Observers

Fingerprint

Dive into the research topics of 'Detection of False Data Injection and Series Arc Faults in DC Microgrids Based on Unknown Input Observers'. Together they form a unique fingerprint.

Cite this