An algorithm for removing trends from power-system oscillation data

When analyzing the electromechanical dynamic properties of power-system field-measurement data using signal processing techniques, it is often useful to identify and remove the slow trends within the data. This paper proposes an iterative non-linear trend identification algorithm. The proposed method adapts the upper and lower envelope idea proposed by empirical mode decomposition (EMD) method to identify the trend. The comparison with conventional trend identification methods are made with simulation data. Also, the proposed algorithm is applied to a field measurement data set to evaluate its performance.