  Forced oscillation event in power grids refers to a state where
malfunctioning or abnormally operating equipment causes persisting periodic
disturbances in the system. While power grids are designed to damp most of
perturbations during standard operations, some of them can excite normal modes
of the system and cause significant energy transfers across the system,
creating large oscillations thousands of miles away from the source.
Localization of the source of such disturbances remains an outstanding
challenge due to a limited knowledge of the system parameters outside of the
zone of responsibility of system operators. Here, we propose a new method for
locating the source of forced oscillations which addresses this challenge by
performing a simultaneous dynamic model identification using a principled
maximum likelihood approach. We illustrate the validity of the algorithm on a
variety of examples where forcing leads to resonance conditions in the system
dynamics. Our results establish that an accurate knowledge of system parameters
is not required for a successful inference of the source and frequency of a
forced oscillation. We anticipate that our method will find a broader
application in general dynamical systems that can be well-described by their
linearized dynamics over short periods of time.

Adaptation and Self-Organizing Systems;Optimization and Control