AUTHORS: Jumana Alshawawreh, Hisham Alrawashdeh
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ABSTRACT: Kalman filter is widely used in Power system for harmonics estimation, where the performance of Kalman filter depends on having an accurate model of the system harmonics to predict the next state variables based on the current states. The model of each harmonic signal is easy and only two state variables are required, but if the harmonic model doesn't include all the harmonics in the measured signal, this will cause error in the estimated states by Kalman filter, in most of previous researches the Mean Square Error (MSE) was calculated to show how much the estimated signal is closed to the actual signal, but the MSE is not enough to determine the source of the error whether it is resulted from an error in the estimated signal frequency or its amplitude. In this paper a frequency analysis using Fast Fourier Transform (FFT) for the estimated states of the Kalman filter was performed to understand the source of the error, after that a modification in Kalman filter calculation is proposed to reduce the error based on the frequency analysis.
KEYWORDS: - Kalman filter, FFT, Harmonics, Power System
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