Step Change Detection for Improved ROCOF Evaluation of Power System Waveforms

In the analysis of power grid waveforms, the presence of amplitude or phase steps can disrupt the estimation of frequency and rate-of-change-of-frequency (ROCOF). Standard methods based on phasor-models fail in the extraction of signal parameters during these signal dynamics, often yielding large frequency and ROCOF deviations. To address this challenge, we propose a technique that approximates components of the signal (e.g., amplitude and frequency variations) using dictionaries based on parameterized models of common signal dynamics. Distinct from a previous iteration of this method developed by the authors, the proposed technique allows for the identification of multiple steps in a window, as well as the presence of interfering tones. The method is shown to improve signal reconstruction when applied to real-world waveforms, as compared to standard static and dynamic phasor-based algorithms.