An enhanced FFT-based parametric (E-FFT) algorithm suitable for on-line harmonic analysis of electrical power systems is presented. This E-FFT algorithm exploits its iteration loops in combination with the characteristic of steep-descent gradient search strategy, to limit the sensitiveness of the total harmonic distortion caused by changes in the number of parameters involved in distorted signal models. The E-FFT algorithm performs reasonably well with short data record length. Unlike most gradient-descent search algorithms for a global minimum point, the proposed E-FFT algorithm averts the risk of being trapped at any local minimum point in the search path. The E-FFT algorithm differs from other FFT and Kalman filter based tracking algorithms, in that it is able to provide simultaneous tracking of co-variations between integer and non-integer (sub) harmonics in a small number of iteration steps. Numerical illustrative examples demonstrating the operation of this E-FFT algorithm and its simulated performance results are also presented.
[1]
Kit Po Wong,et al.
Wavelet-transform-based algorithm for harmonic analysis of power system waveforms
,
1999
.
[2]
V. M. Moreno Saiz,et al.
Application of Kalman filtering for continuous real-time tracking of power system harmonics
,
1997
.
[3]
T. T. Nguyen.
Parametric harmonic analysis
,
1997
.
[4]
Peter T. Gough,et al.
A fast spectral estimation algorithm based on the FFT
,
1994,
IEEE Trans. Signal Process..
[5]
Tung-Sang Ng,et al.
Gradient-based adaptive IIR notch filtering for frequency estimation
,
1990,
IEEE Trans. Acoust. Speech Signal Process..
[6]
Y. Chan,et al.
A parameter estimation approach to estimation of frequencies of sinusoids
,
1981
.