Estimation of electromechanical modes of power system using ARMA model based on cross spectrum

In recent years, as power systems have become larger, power oscillations have become multifaceted, and so online Dynamic Security Assessment (DSA) has become essential to estimate these low-frequency electromechanical modes. To use this information for stabilization control of angle stability, it is important to obtain information on not only the frequency and damping of those modes but also the relative phase relation between each generator. This paper introduces a technique to estimate the relative phase relation of generators from time series data. The proposed method is applied to a two-variable ARMA model to estimate the low-frequency modes, and is applied to the cross spectrum to estimate the eigenvector efficiently. The proposed technique is verified by numerical examples with the IEEE 39-Bus system and the West 30-machine system model (115-Bus) which simulates the power system of Japan, and is compared with the eigenvector estimated by eigenvalue analysis.