Abstract
This paper presents a method for predictive out-of-step (OOS) tripping based on synchrophasors. The OOS condition is
predicted based on information of the ongoing power oscillation, where the input signal can be either the phase angle between
two nodes in the power grid or the current magnitude of a line. The proposed algorithm first detects power swing by comparing
the oscillation magnitude with a set threshold. Once a power swing is detected, a damping coefficient associated to the power
oscillation is estimated to assess its stability. The oscillation is predicted unstable and eventually will lead to OOS condition
when both the damping coefficient and the input signal are larger than set thresholds. The tuning of these thresholds is relatively
simple and straightforward. Results from simulations in the Kundur system and the Nordic 44 model demonstrate that the
proposed algorithm is able to correctly predict coming OOS conditions from the analysis of power swings in the power grid.
predicted based on information of the ongoing power oscillation, where the input signal can be either the phase angle between
two nodes in the power grid or the current magnitude of a line. The proposed algorithm first detects power swing by comparing
the oscillation magnitude with a set threshold. Once a power swing is detected, a damping coefficient associated to the power
oscillation is estimated to assess its stability. The oscillation is predicted unstable and eventually will lead to OOS condition
when both the damping coefficient and the input signal are larger than set thresholds. The tuning of these thresholds is relatively
simple and straightforward. Results from simulations in the Kundur system and the Nordic 44 model demonstrate that the
proposed algorithm is able to correctly predict coming OOS conditions from the analysis of power swings in the power grid.