VELARDE RUEDA, PABLO ANIBAL, Hernández-Rivera, A. , Zafra-Cabeza, A. , Bordons Alba, C.
No
Conference Paper
Científica
01/01/2025
2-s2.0-105021827818
This work proposes a cyber-resilient Distributed Model Predictive Control framework to improve microgrid security and operational reliability against cyber threats. It specifically addresses manipulation attacks on the weight negotiation process within the Alternating Direction Method of Multipliers (ADMM) algorithm, where a malicious agent can alter weight updates, resulting in a cyber-attack. To counter these threats, the proposed approach integrates anomaly detection mechanisms that analyze negotiation patterns and identify malicious behavior through residual analysis. Upon detecting deviations in critical operational parameters, this system implements targeted mitigation actions to minimize the attack's impact. Simulation results demonstrate the effectiveness of this approach in detecting and mitigating ADMM-based manipulation attacks, emphasizing the necessity of integrating cybersecurity mechanisms into distributed control frameworks for enhanced microgrid resilience. © © 2025 The Authors.
Anomaly detection; Computer crime; Control theory; Crime; Cybersecurity; Distributed parameter control systems; Industrial electronics; Microgrids; Model predictive control; Network security; Alternating directions method of multipliers; Control framework; Cyber threats; Cyber-attacks; Distributed Model predictive Control; Distributed MPC; Faults detection; Microgrid; Mitigation; Operational reliability; Copyrights