Abstract: This paper aims to present the reviews of the
application of neural network in shunt active power filter (SAPF).
From the review, three out of four components of SAPF structure,
which are harmonic detection component, compensating current
control, and DC bus voltage control, have been adopted some of
neural network architecture as part of its component or even
substitution. The objectives of most papers in using neural network in
SAPF are to increase the efficiency, stability, accuracy, robustness,
tracking ability of the systems of each component. Moreover,
minimizing unneeded signal due to the distortion is the ultimate goal
in applying neural network to the SAPF. The most famous
architecture of neural network in SAPF applications are ADALINE
and Backpropagation (BP).
Abstract: The paper deals with the comparison study of
harmonic detection methods for a shunt active power filter. The
%THD and the power factor value at the PCC point after
compensation are considered for the comparison. There are three
harmonic detection methods used in the paper that are synchronous
reference frame method, synchronous detection method, and DQ axis
with Fourier method. In addition, the ideal current source is used to
represent the active power filter by assuming an infinitely fast
controller action of the active power filter. The simulation results
show that the DQ axis with Fourier method provides the minimum
%THD after compensation compared with other methods. However,
the power factor value at the PCC point after compensation is slightly
lower than that of synchronous detection method.