Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/62267
Title: Harmonic estimation in a power system using adaptive perceptrons
Authors: Dash, P.K. 
Swain, D.P.
Routray, A.
Liew, A.C. 
Keywords: Adaline
Adaptive perceptrons
Harmonic estimation
Neural networks
Power systems
Issue Date: 1996
Source: Dash, P.K.,Swain, D.P.,Routray, A.,Liew, A.C. (1996). Harmonic estimation in a power system using adaptive perceptrons. IEE Proceedings: Generation, Transmission and Distribution 143 (6) : 565-574. ScholarBank@NUS Repository.
Abstract: The paper presents an adaptive neural network approach for the estimation of harmonic components of a power system. The neural estimator is based on the use of an adaptive perceptron comprising a linear adaptive neuron called Adaline. The learning parameters in the proposed algorithm are adjusted to force the error between the actual and desired outputs to satisfy a stable difference error equation. The estimator tracks the Fourier coefficients of the signal data corrupted with noise and decaying DC components very accurately. Adaptive tracking of harmonic components of a power system can easily be done using this algorithm. Several numerical tests have been conducted for the adaptive estimation of harmonic components of power system signals mixed with noise and decaying DC components. Data from a laboratory test is used to validate the performance of this new approach. © IEE, 1996.
Source Title: IEE Proceedings: Generation, Transmission and Distribution
URI: http://scholarbank.nus.edu.sg/handle/10635/62267
ISSN: 13502360
Appears in Collections:Staff Publications

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