Power Grid Resilience Against False Data Injection Attacks

Smart Grid security has motivated numerous researches from multiple disciplines. Among the recently discovered security challenges, the False Data Injection (FDI) has drawn great attention from power and energy, computer, and communication research community, because of its potential to manipulate measurements in state estimation (SE) without being identified by conventional bad data detection (BDD) methods. Despite the current focus on attack scheme studies in literature, the actual damage and system resilience to FDI attacks are yet to be evaluated. This paper analyzes grid resilience against FDI by formulating random FDI attacks with different magnitudes and number of false data. A steady-state AC power flow based blackout model is used to simulate misinformed system response after FDI and potential cascading blackouts in power transmission networks. Line outages, load shed, and voltage violations are evaluated on IEEE 300-bus system. Preliminary results have shown that while FDI attacks are considered severe potential threats in the smart grid, a power system can be resilient to FDI attacks in terms of blackout risk and cascading outages, yet the transient voltage stability could suffer from severe FDI attacks.