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

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.