Advanced windowed interpolated FFT algorithms for harmonic analysis of electrical power system

Fast Fourier Transform (FFT) is used to obtain the Fourier spectrum of a periodic signal, but it is well known that special care must be taken to avoid severe distortions introduced by the sampling process. The major errors associated with this algorithm are spectral leakage and picket fence effect. This paper discusses the advancement in FFT algorithms for harmonic analysis in power system by applying windowed interpolation techniques. It is observed that the application of different WIFFT algorithms has different effects on the measuring accuracy. The advanced minimized sidelobe window (MSW) algorithm has better performance characteristics when compared to the conventional hanning and hamming windows adopted for harmonic analysis. By considering the practical harmonic data the hanning, hamming and MSW algorithms are validated using matlab programming. The simulation results demonstrate the effectiveness of hanning, hamming and MSW by considering the magnitude and phase angle error variations with respect to the harmonic order.