An Efficient Prony-Based Solution Procedure for Tracking of Power System Voltage Variations

Some advanced parametric methods for assessing waveform distortion in a smart grid with renewable generation

“…In fact, starting from the consideration that the damping factors and the frequencies of spectral components in power system applications are slightly variable versus time [25,[39][40][41][42][43], the estimation of frequencies is conducted only a few times, and the damping factors are assumed to be constant along the entire signal to be analyzed [31,32].…”

New ESPRIT-based method for an efficient assessment of waveform distortions in power systems

“…The analysis of time-varying waveforms in several power system applications has shown that in most cases the spectral components of the waveform are characterized by frequencies that are much less variable versus time than amplitudes [11,12,15,[19][20][21].…”

“…The non-parametric methods, as is the case for STFT-based methods, provide only a rough estimation of the waveform distortions, and, since their frequency resolutions are fixed, the detection of interharmonics and sub-harmonics is particularly difficult. The parametric methods, e.g., the Prony and ESPRIT methods, were proposed for an accurate assessment of spectral components [11][12][13][14][15][16][17][18][19][20][21]. In the case of the distortion of a timevarying waveform, the sliding window (SW) parametric methods use a window that slides forward successively over time to perform the spectral analysis.…”

“…In doing so, these methods provide improved estimation of harmonics and interharmonics at the cost of significantly increased computational requirements. In [14,15], modified versions of the Prony's method were proposed to reduce the computational efforts and guarantee acceptable accuracy, but the computational time still exceeded that of the STFT-based methods. In [17], an adaptive algorithm based on the SW ESPRIT method was proposed to estimate the order of the model in each data block and then adjust the size of the autocorrelation matrix.…”

“…The method proposed in [21] starts from the consideration that the damping factors and the frequencies of the spectral components in power system applications vary slightly with time [9,[11][12][13][14][15][19][20][21][22][23] and assumes that the damping factors of the spectral components are equal to zero and that the frequencies are constant and known a priori; this method seems to be particularly interesting because it requires computational effort that is comparable to that required by the traditional STFT-based methods while guaranteeing adequate accuracy in the assessment of the spectral components.…”