Hybrid FFT-ADALINE algorithm with fast estimation of harmonics in power system

Hybrid fast Fourier transform Adaptive LINear Element (FFT-ADALINE) algorithm for fast and accurate estimation of harmonics is proposed in this study. The FFT method can perform fast conversion from time domain to frequency domain, but it cannot respond immediately to any change of the measured harmonics due to the utilisation of buffer. Meanwhile, ADALINE has better capability to respond immediately due to its learning ability, but its settling time is about two cycles of the measurement signal. In the proposed method, both of the aforementioned algorithms are combined for harmonic estimation where it is able to respond immediately to any change of the measured harmonics and the settling time is reduced to half cycle of the measurement signal. The theory of the proposed algorithm is the application of FFT with weights updating rule to reduce the error of ADALINE instantaneously. The robustness of the proposed method is simulated via MATLAB Simulink. The validity of the simulation work is further proven by the experimental work, which has been done with Chroma programmable AC source model 6590 and non-linear load operations. The proposed algorithm operates in good and accurate performance with the settling time is within half cycle.

[1]  Mototaka Sone,et al.  An application of neural network for harmonic detection in active filter , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

[2]  M. Omair Ahmad,et al.  A new radix-2/8 FFT algorithm for length-q×2m DFTs , 2004, IEEE Trans. Circuits Syst. I Regul. Pap..

[3]  G. Z. Peng,et al.  A new vector draft method for harmonic source detection at point of common coupling , 2014, 2014 IEEE 8th International Power Engineering and Optimization Conference (PEOCO2014).

[4]  Gary W. Chang,et al.  A two-stage ADALINE for harmonics and interharmonics measurement , 2010, 2010 5th IEEE Conference on Industrial Electronics and Applications.

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

[6]  G. Chang,et al.  Measuring power system harmonics and interharmonics by an improved fast Fourier transform-based algorithm , 2008 .

[7]  R. Sindal,et al.  Simulation and Analysis of DIT FFT Algorithm for Spartan 3 FPGA , 2013, 2013 International Conference on Communication Systems and Network Technologies.

[8]  Stanislaw Osowski,et al.  Neural network for estimation of harmonic components in a power system , 1992 .

[9]  Zhengyan Liu,et al.  Study on harmonic detection method based on FFT and wavelet transform , 2010, 2010 2nd International Conference on Signal Processing Systems.

[10]  S. Bertram.  On the derivation of the fast Fourier transform , 1970 .

[11]  Paul S. Wright,et al.  Short-time Fourier transforms and Wigner-Ville distributions applied to the calibration of power frequency harmonic analyzers , 1999, IEEE Trans. Instrum. Meas..

[12]  Mohd Amran Mohd Radzi,et al.  Neural Network and Bandless Hysteresis Approach to Control Switched Capacitor Active Power Filter for Reduction of Harmonics , 2009, IEEE Transactions on Industrial Electronics.

[13]  Thomas Ellinger,et al.  Dynamic Interaction Analysis of APF Systems , 2014, IEEE Transactions on Industrial Electronics.

[14]  Wenle Zhang,et al.  System Identification Based on a Generalized ADALINE Neural Network , 2007, 2007 American Control Conference.

[15]  P. J. Rose,et al.  Harmonics: the effects on power quality and transformers , 1994 .

[16]  Bhim Singh,et al.  Implementation of Neural-Network-Controlled Three-Leg VSC and a Transformer as Three-Phase Four-Wire DSTATCOM , 2011 .

[17]  Vinod Khadkikar,et al.  Optimal Current Harmonic Extractor Based on Unified ADALINEs for Shunt Active Power Filters , 2014, IEEE Transactions on Power Electronics.

[18]  E.F. El-Saadany,et al.  Envelope tracking techniques for FlickerMitigation and Voltage regulation , 2004, IEEE Transactions on Power Delivery.

[19]  H. Lin,et al.  Inter-Harmonic Identification using Group-Harmonic Weighting Approach Based on the FFT , 2008, IECON 2007 - 33rd Annual Conference of the IEEE Industrial Electronics Society.

[20]  Vinod Khadkikar,et al.  Application of Artificial Neural Networks for Shunt Active Power Filter Control , 2014, IEEE Transactions on Industrial Informatics.

[21]  Dushan Boroyevich,et al.  Wavelet Transform as an Alternative to the Short-Time Fourier Transform for the Study of Conducted Noise in Power Electronics , 2008, IEEE Transactions on Industrial Electronics.

[22]  Avik Bhattacharya,et al.  A Shunt Active Power Filter With Enhanced Performance Using ANN-Based Predictive and Adaptive Controllers , 2011, IEEE Transactions on Industrial Electronics.