Performance Analysis of Frequency Estimation Using Different Adaptive Filters Techniques

Abstract

The Electrical power system frequency is an important parameter. The frequency of operation is not constant but it varies depending upon the load conditions. In the operating, controlling and monitoring of electric devices power system parameters are having great contribution. So it is very important to accurately measure this slowly varying frequency. Under steady-state conditions the total power generated by power stations is equal to system load and losses. Frequency can deviate from its nominal value due to sudden appearance of generation-load mismatches. Frequency is a vital parameter which influences different relay functionality of power system. In this paper study was made to estimate the frequency of measuring voltage or current signal in presence of random noise and distortion. Here we are first using linear techniques such as least mean square (LMS), algorithm for measuring the frequency from the distorted voltage signal. Then comparing these results with nonlinear techniques such as nonlinear least mean square (NLMS), and UNANR algorithms with different modulation techniques was Amplitude Modulation. Signal performance parameter PSNR measured and compared with respect to Signal to Noise Ratio. The performances of these algorithms are studied through MATLAB R2012a simulation