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Resilient Consensus Control Design for DC Microgrids against False Data Injection Attacks Using a Distributed Bank of

Yousof Barzegari1, Jafar Zarei1,2, Roozbeh Razavi-Far2

  • 1Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz 71557-13876, Iran.

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Summary
This summary is machine-generated.

This study introduces a new method for detecting false data injection attacks (FDIA) in DC microgrids. The algorithm enhances system security by identifying and mitigating malicious data, ensuring reliable operation of distributed energy resources.

Keywords:
DC microgridattack-resilient controlboost converterfalse data injection cyber attacksliding mode observer

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Area of Science:

  • Electrical Engineering
  • Control Systems
  • Cybersecurity

Background:

  • Microgrids are increasingly vulnerable to cyberattacks, specifically false data injection attacks (FDIA).
  • Distributed boost converters in DC microgrids are susceptible to voltage data manipulation, impacting grid stability.
  • Conventional consensus algorithms lack robustness against sophisticated FDIA.

Purpose of the Study:

  • To develop and validate a novel algorithm for detecting FDIA in DC microgrids.
  • To enhance the resilience of microgrid control systems against cyber threats.
  • To ensure the reliable operation of distributed energy resources under attack scenarios.

Main Methods:

  • Utilizing a bank of sliding mode observers to estimate neighboring agent states.
  • Implementing a detection mechanism based on state estimation and communication data.
  • Replacing conventional consensus rules with attack-resilient control schemes.

Main Results:

  • The proposed algorithm successfully detects false data injection attacks in real-time simulations.
  • Experimental verification with three boost converters confirms the algorithm's effectiveness.
  • The control scheme demonstrates resilience against consensus deviation caused by FDIA.

Conclusions:

  • The developed algorithm provides an effective solution for FDIA detection in DC microgrids.
  • The proposed method enhances the security and reliability of microgrid operations.
  • This research contributes to the development of more robust and secure smart grid technologies.