AN ADAPTIVE LINEAR COMBINER FOR ONLINE TRACKING OF POWER-SYSTEM HARMONICS

The paper presents a new approach for the estimation of harmonic compo nents of a power system using a linear adaptive neuron called Adaline. The learning parameters in the proposed neural estimation algorithm a re adjusted to force the error between the actual and desired outputs to satisfy a stable difference error equation. The estimator tracks th e Fourier coefficients of the signal data corrupted with noise and dec aying de components very accurately. Adaptive tracking of harmonic com ponents of a power system can easily be done using this algorithm. Sev eral numerical tests have been conducted for the adaptive estimation o f harmonic components of power system signals mixed with noise and dec aying de components.