Detection of Cyber-Physical Attacks Using Optimal Recursive Least Square in an Islanded Microgrid

Abstract

Islanded microgrids (IMGs) are defined as low-inertia systems compared to conventional power grids due to existing inverter-based topologies and lack of heavy rotational masses in their structures. In this regard, IMGs require an accurate load frequency control (LFC) scheme to regulate the frequency response through a cyber layer on top of the physical layer. This multi-layer structure and the sensitivity of LFC schemes to any disturbance, however, makes MGs an appealing target for a variety of cyber-physical attacks (CPAs). This paper introduces an online detection algorithm for CPAs in IMGs by the use of a recursive least square method along with forgetting factor (RLS-FF). The simulation results verify the performance of the developed detection schemes, particularly when the RLS-FF approach coefficients, i.e., covariance matrix and forgetting factor are optimally selected using particle swarm optimization (PSO) algorithm.