Power system frequency estimation accuracy of improved DFT-based algorithms over short intervals

Recent research results in the field of algorithms for Phasor Measurement Units (PMUs) have pointed out that the estimators based on dynamic phasor models are generally preferable to track waveform parameters over time. This statement is definitely true when amplitude, phase, frequency and rate of change of frequency (ROCOF) fluctuate significantly within the observation interval used to estimate them. Unfortunately, these estimation algorithms can be very sensitive to narrow-band disturbances, unless these contributions are explicitly included in the model at the expense of a larger computational complexity. However, if the observation intervals are so short that the waveform parameter variations each of them are minor, then algorithms based on static phasor model can provide accurate results with a reasonably low computational burden. Since the waveform fundamental frequency is a key parameter for power systems monitoring and control, in this paper the estimation accuracy of three classes of state-of-the-art algorithms based on a static signal model is analyzed and compared when only few waveform cycles affected by both steady-state disturbances (e.g. harmonics) and amplitude or phase oscillations are collected.