Extracting steady state harmonic components from synchrophasor data: Comparison among recursive filtering methods

This paper aims to evaluate the effectiveness of recursive filtering techniques in order to increase the accuracy of synchronized harmonic data provided by PMUs (Phasor Measurement Units). The recursive filters are known by their capability of reducing noise, compensating for missing data and filtering outliers from PMU input signals for real-time data processing. In this work, the moving average, the first order low-pass and Kalman filters are compared and their advantages and potentialities are discussed considering a performance analysis of these recursive filtering techniques for PMU data signals.