Future power networks will be characterized by safe and reliable
functionality against physical malfunctions and cyber attacks. This paper
proposes a unified framework and advanced monitoring procedures to detect and
identify network components malfunction or measurements corruption caused by an
omniscient adversary. We model a power system under cyber-physical attack as a
linear time-invariant descriptor system with unknown inputs. Our attack model
generalizes the prototypical stealth, (dynamic) false-data injection and replay
attacks.
This work presents a distributed method for control centers in a power
network to estimate the operating condition of the power plant, and to
ultimately determine the occurrence of threatening situations. State estimation
has been recognized to be a fundamental task for network control centers to
ensure correct and safe functionalities of power grids. We consider (static)
state estimation problems, in which the state vector consists of the voltage
magnitude and angle at all network buses.