DFT-based phasor estimator using a MAF with a phase-lead compensator

Abstract

Due to the advancing complexity of the electrical power system, phasor estimators are becoming essential for measuring its dynamics. Many estimators are now needed to effectively monitor some grid, specially for the wireless sensor networks development. However, the smart sensors comprising such networks are low-cost devices and they are only capable of running low computationally loaded algorithms. In consequence, complex algorithms, like the ones based on Kalman filters and the wavelet transform, cannot be applied and a simpler approach is needed. The Fourier filter emerges as a solution since it has a low computational load and it incorporates a moving average filter, whose main advantage is that it can eliminate harmonics. Nevertheless, the moving average filter causes a significant phase delay that is undesirable in fast-response applications. Therefore, in this thesis it is proposed to add a phase-lead compensator to the moving average filter to solve its phase delay problem, while preserving its harmonic rejection ability and the algorithm’s simplicity. This estimator was compared with the conventional Fourier filter and the cosine filter in IEEE C37.118.1 standardized tests to analyze its performance under harmonic contamination, amplitude, and phase angle step changes. After tuning the compensator, the proposal did meet all the standard requirements and showed a slightly faster response than its non-compensated version, yet increasing the algorithm’s execution time. Also, the proposal was tested over the IEEE 13 node test feeder, showing a faster response than the Fourier filter and the cosine filter.