New phasor estimator in the presence of harmonics, dc offset, and interharmonics

Abstract

This paper proposes the use of Artificial Neural Networks (ANN) to estimate the magnitude and phase of fundamental component of sinusoidal signals in the presence of harmonics, sub-harmonics and DC offset. The proposed methodology uses a preprocessing that is able to generate a signal that represents the influence of sub-harmonics and DC offset in the fundamental component. This signal is used as input of ANN, which estimate the influence of that signal in quadrature components. Using this information, corrections can be made in quadrature components then the real value of phasor of the fundamental component is estimated. The performance of the proposed algorithm was compared with classical methods such as DFT, using one and two cycles, and LES. The results showed that the proposed method is accurate and fast. The methodology can be used as a phasor estimator of system with poor Power Quality indices for monitoring, control and protection applications.