Analyzing Replay Attack Impact in DC Microgrid Consensus Control: Detection and Mitigation by Kalman-Filter-Based Observer

Abstract

This paper adopts a Direct Current (DC) Microgrid with a consensus-based secondary control strategy to efficiently manage the microgrid, ensuring precise voltage regulation and fair power distribution among Distributed Energy Resources (DERs). The consensus approach employs a communication network to establish a Cyber layer for DER information exchange and harmonize the entire system to achieve a common goal. However, this cyber layer's vulnerability could destabilize the interconnected control system and lead to the whole system being unsynchronized. The paper explores replay attacks conducted in the path of the communication link between interconnected Distributed Generation Units (DGUs), demonstrating their impact on secondary control using simulations and real-time experiments. A method leveraging Distributed Kalman Filter observers for attack detection is proposed which requires low computational demand to suit the real-time application, while an attack mitigation technique using observer-generated residues with the optimal condition is implemented. Validation is conducted through both MATLAB simulations and realtime OPAL-RT experiments, confirming the proposed system's effectiveness.

False Data Injection Attack Detection and Mitigation Using Nonlinear Autoregressive Exogenous Input-Based Observers in Distributed Control for DC Microgrid

“…In this scenario, a microgrid is under consideration, comprising four distributed generation units labeled as DG1, DG2, DG3, and DG4, interconnected via a transmission line and communication link. DC current and voltage estimation for each unit relies on inputs from the DC voltages of other units, as indicated in equation (8). Specifically, in the context of a DC microgrid with K sources, the DC voltage of unit n serves as the output generated by the NARX network estimator for DC voltage.…”

“…Understanding CPS intricacies is crucial for safeguarding microgrid integrity and security [6]. Despite these advancements, microgrids face cyber threats such as False Data Injection Attacks (FDIA) [7], replay attacks [8], denial of service (DoS) attacks [9], and stealthy attacks and environmental adversaries [10], jeopardizing stability and reliability [11,12]. FDIA, particularly subtle, manipulate critical sensor data to deceive controllers without immediate detection [13].…”