Analysis of Adaptive Linear Neural Network (Adaline) In Power System Harmonics Signal

Pratap Sekhar Puhan*, Sandeep S D**, D.Sutar***
Periodicity:April - June'2018


Estimation of power system parameter plays an important role in the modern power system. In this paper estimation of harmonics components in a power system synthetic signal is done by an improved estimation techniques called as ADALINE. This neural estimator basically uses an adaptive interpreted linear neuron. Learning parameter is adjusted to keep the difference between the Real values and Expected values to satisfy the difference arises due to error equation. Tracking of the fourier co-efficent of the proposed signal, which is also constitutes a noise and DC decaying component can be done easily and accurately using the proposed algorithm. To verify the effectiveness of the proposed algorithm estimation of amplitude as well as Phase of fundamental and harmonics is carried out. The simulation results obtained are encouraging to work more on estimation of signal.


Harmonics, Estimation, Adaline, Neural Network, Weight Vector, Power Quality.

How to Cite this Article?

Puhan, P. S., Sandeep, S. D., and Sutar, D. (2018). Analysis of Adaptive Linear Neural Network (Adaline) In Power System Harmonics Signal. i-manager’s Journal on Electrical Engineering, 11(4), 35-42.


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