Real-Time Phasor Estimation via the Taylor-Fourier's Subspace

This paper focuses on the real-time phasor estimation via Taylor-Fourier’s Subspace (TFS) on a low-cost embedded platform. Signal processing is carried out using a sliding window for the sampled signal by the Analog-to-Digital Converter (ADC). A digital Taylor-Fourier filter designed using the TFS, deals with the extraction of the dynamic phasor estimates such as: amplitude, phase angle, frequency, and rate of change of frequency (ROCOF). Then, a Python-based interface is developed to display the real-time monitoring for those parameters. Finally, results exhibit the performance of the implemented phasor estimator attaining reliable estimates for both simulated and real signals, and tracking accurately the changes in amplitude, phase and frequency.