Measurement based power system dynamics prediction with multivariate AutoRegressive Model

Power system dynamics prediction is important for online situation awareness and adaptive control. Model-based simulation is not applicable for dynamics prediction due to constant change of network configuration. With more and more Phasor Measurement Units (PMU), power system dynamics can be studied with pure measurement data. This paper proposes a dynamics prediction method based on measurement data. A mulit-input multi-output Multivariate AutoRegressive model (MAR) is developed and dynamics prediction procedure is proposed. Both simulation data and field measurement data are tested. Examples show that the proposed method can predict power system dynamics with high accuracy for simulation data and give reasonable result for measurement data. It provides an alternative approach to study power system dynamics.