ONLINE PREDICTION OF POWER SYSTEM TRAJECTORIES FROM PHASOR-MEASUREMENT-UNIT (PMU) DATA

Abstract

This paper proposes an online method to integrate the trajectories of differential-algebraic equations in the context of networked power systems. We predict these trajectories from a real-time data stream generated by phasor measurement units, combining newly incoming data with past information. For this purpose, we propose a stochastic optimization technique that incorporates new data as they become available, trading-off measurement errors for modeling uncertainty. The method is tested on a benchmark system of 39 buses and 10 generators being able to anticipate the system recovery from a three-phase-to-ground short-circuit.