  This work addresses the problem of transient stabilization of a power grid,
following a destabilizing disturbance. The model considered is the cascade
interconnection of seven New England test models with the disturbance (e.g., a
powerline failure) occurring in the first grid and propagating forward,
emulating a wide-area blackout. We consider a data-driven control framework
based on the Koopman operator theory, where a linear predictor, evolving on a
higher dimensional (embedded) state-space, is built from observed data and
subsequently used within a model predictive control (MPC) framework, allowing
for the use of efficient computational tools of linear MPC to control this
highly nonlinear dynamical system.
