  Recently, moving target defence (MTD) has been proposed to thwart false data
injection (FDI) attacks in power system state estimation by proactively
triggering the distributed flexible AC transmission system (D-FACTS) devices.
One of the key challenges for MTD in power grid is to design its real-time
implementation with performance guarantees against unknown attacks. Converting
from the noiseless assumptions in the literature, this paper investigates the
MTD design problem in a noisy environment and proposes, for the first time, the
concept of robust MTD to guarantee the worst-case detection rate against all
unknown attacks. We theoretically prove that, for any given MTD strategy, the
minimal principal angle between the Jacobian subspaces corresponds to the
worst-case performance against all potential attacks. Based on this finding,
robust MTD algorithms are formulated for the systems with both complete and
incomplete configurations. Extensive simulations using standard IEEE benchmark
systems demonstrate the improved average and worst-case performances of the
proposed robust MTD against state-of-the-art algorithms. All codes are
available at https://github.com/xuwkk/Robust_MTD.
