Mahalanobis distance-based robust approaches against false data injection attacks on dynamic power state estimation
Jing Lin,
Kaiqi Xiong
Abstract:State estimation plays a crucial role in the daily operation of power systems. Although many researchers have studied false data injection (FDI) attacks in power state estimation, current state estimation approaches are still highly vulnerable to FDI attacks. Currently, most existing studies on FDI attacks focus on static state estimation (SSE), where power system states are not changed with time, and one of them includes the discovery of three efficient FDI attacks that can introduce arbitrary large errors in… Show more
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