Measuring power system harmonics and interharmonics by an improved fast Fourier transform-based algorithm

The fast Fourier transform (FFT) has been widely used for the signal processing because of its computational efficiency. Because of the spectral leakage and picket-fence effects associated with the system fundamental frequency variation and improperly selected sampling time window, a direct application of the FFT algorithm with a constant sampling rate may lead to inaccurate results for continuously measuring power system harmonics and interharmonics. An improved FFT-based algorithm to measure harmonics and interharmonics accurately is proposed. In the proposed algorithm, a frequency-domain interpolation approach is adopted to determine the system fundamental frequency, and the interpolatory polynomial method is applied to reconstruct the sampled time-domain signal; it is followed by using the FFT to calculate the actual harmonic components. Then, the frequency-domain interpolation is again applied to find the interharmonic components. The performance of the proposed algorithm is validated by testing the actual measured waveforms. Results are compared with those obtained by directly applying a typical FFT algorithm and by the IEC grouping method. It shows that the solutions determined by the proposed algorithm are more accurate, and a reasonable computational efficiency is maintained.

[1]  Adly Girgis,et al.  A Quantitative Study of Pitfalls in the FFT , 1980, IEEE Transactions on Aerospace and Electronic Systems.

[2]  J. Douglas Faires,et al.  Numerical Analysis , 1981 .

[3]  P. Djurić,et al.  Frequency tracking in power networks in the presence of harmonics , 1993 .

[4]  Saifur Rahman,et al.  An adaptive linear combiner for on-line tracking of power system harmonics , 1996 .

[5]  Aurobinda Routray,et al.  Harmonic estimation in a power system using adaptive perceptrons , 1996 .

[6]  J. Rezmer,et al.  Real-time determination of power system frequency , 1996, Quality Measurement: The Indispensable Bridge between Theory and Reality (No Measurements? No Science! Joint Conference - 1996: IEEE Instrumentation and Measurement Technology Conference and IMEKO Tec.

[7]  V. M. Moreno Saiz,et al.  Application of Kalman filtering for continuous real-time tracking of power system harmonics , 1997 .

[8]  M. Akke.  Frequency Estimation by Demodulation of No Complex Signals , 1997, IEEE Power Engineering Review.

[9]  Sanjib Kumar Panda,et al.  Fast estimation of voltage and current phasors in power networks using an adaptive neural network , 1997 .

[10]  T. Lobos,et al.  Power system harmonics estimation using linear least squares method and SVD , 1999, IMTC/99. Proceedings of the 16th IEEE Instrumentation and Measurement Technology Conference (Cat. No.99CH36309).

[11]  David W. P. Thomas,et al.  Evaluation of frequency tracking methods , 2001 .

[12]  Dusan Agrez,et al.  Weighted multipoint interpolated DFT to improve amplitude estimation of multifrequency signal , 2002, IEEE Trans. Instrum. Meas..

[13]  R. Yang,et al.  Optimal interpolating windowed discrete Fourier transform algorithms for harmonic analysis in power systems , 2003 .

[14]  Hsiung Cheng Lin.  Intelligent neural-network-based adaptive power-line conditioner for real-time harmonics filtering , 2004 .

[15]  A. Testa,et al.  On the Processing of harmonics and interharmonics: using Hanning window in standard framework , 2004, IEEE Transactions on Power Delivery.

[16]  A. Testa,et al.  Desynchronized Processing technique for Harmonic and interharmonic analysis , 2004, IEEE Transactions on Power Delivery.

[17]  G.W. Chang,et al.  An analytical approach for characterizing harmonic and interharmonic currents generated by VSI-fed adjustable speed drives , 2005, IEEE Transactions on Power Delivery.

[18]  H. Lesani,et al.  New technique for frequency and amplitude estimation of power system signals , 2005 .

[19]  Saeed V. Vaseghi,et al.  Advanced Digital Signal Processing and Noise Reduction: Vaseghi/Advanced Digital Signal Processing and Noise Reduction, 3rd Edition , 2006 .

[20]  Saeed V. Vaseghi,et al.  Advanced Digital Signal Processing and Noise Reduction , 2006 .