A novel method based on Prony analysis for fundamental frequency estimation in power systems

Prony’s method implementation for slow wave identification of electroenterogram signals

“…In addition, the global minimum order p value of each recording point (OGp PRmin ) was obtained using Eq. (15). (15) where OGp PRmin is the average value of the orders of the minimum value at each session for each recording point and the total global order p of the minimum values (OGp Tmin ) is given by Eq.…”

“…The advantage of these techniques with respect to the nonparametric techniques is that they enable determination of the dominant frequency of the signal with better frequency resolution, even with a shorter window of analysis. The application of Prony's method usually applies to power systems [14,15]. However, only a few studies have been performed in the biomedical area using the Prony's method, but not in the gastrointestinal area [16,17].…”

A novel frequency estimation algorithm based on DFT and second derivative

“…Three different frequency variations were considered: the ramp-up change given in Equation (26), the ramp-down change given in Equation (27), and the sinusoidal change given in Equation (28). prony analysis presented in [18] was used to evaluate the performance of the proposed algorithm. The complex prony analysis uses two-cycle samples in the simulations to obtain stable responses, while the proposed algorithm uses 1 + 4/N cycle, which makes the estimation delay small.…”

“…Accurately estimating the varying frequency is essential in many applications, such as load shedding, islanding detection for distributed generators, and control of energy storage systems. For this purpose, many methods have been proposed [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18]. The zero-crossing method is the simplest way to estimate frequency [1,2].…”

“…Thus, the modified zero-crossing method has also been proposed. Other approaches have also been used to estimate the frequency of the power system signal, including Kalman filter [3,4], three-phase phase-locked loop [5][6][7], artificial neural networks [8,9], least square techniques [10,11], newton-type algorithm [12], prony estimation [13], discrete Fourier transform [14][15][16], maximum likelihood method [17], and complex prony analysis [18].…”