Pre-Overload-Graph-Based Vulnerable Correlation Identification under Load Redistribution Attacks

The load redistribution (LR) attack, as a special type of false data injection attacks, aims to distort the results of the security-constrained economic dispatch (SCED) and drive the system to non-optimal or even unsecure operating conditions by injecting false data to the node power injection and branch power flow measurements. The LR attack represents a great danger to the safe and reliable operation of the current power grid where the physical infrastructure is increasingly intertwined with cyber components. In this paper, we propose a novel pre-overload vulnerability graph (POV-graph) approach to systematically assess, evaluate, and quantify the system vulnerability under an LR attack. The proposed approach is formulated based on the specific overloading mechanism of the LR attack as well as their cascading patterns. A set of case studies are performed on the IEEE 39-bus, 118-bus, and RTS-96 systems to validate the effectiveness of the proposed approach. Simulation results have shown, for the first time that, by revealing the vulnerability correlations among branches, the proposed approach allows the system operator to better utilize the defense resources and focus on strengthening a limited number of vulnerable branches to enhance the system's overall security against LR attacks.