Title :
Active power filter control using neural network technologies
Author :
Vazquez, J.R. ; Salmeron, P.
Author_Institution :
Departamento de Ingeniera Electrica, Univ. de Huelva, Spain
fDate :
3/1/2003 12:00:00 AM
Abstract :
A method for controlling an active power filter using neural networks Is presented. Currently, there is an increase of voltage and current harmonics in power systems, caused by nonlinear loads. The active power filters (APFs) are used to compensate the generated harmonics and to correct the load power factor. The proposed control design is a pulse width modulation control (PWM) with two blocks that include neural networks. Adaptive networks estimate the reference compensation currents. On the other hand, a multilayer perceptron feedforward network (trained by a backpropagation algorithm) that works as a hysteresis band comparator is used. Two practical cases with Matlab-Simulink are presented to check the proposed control performance.
Keywords :
active filters; backpropagation; compensation; harmonic distortion; multilayer perceptrons; neurocontrollers; power harmonic filters; power system control; power system harmonics; Matlab-Simulink; active power filter control; backpropagation algorithm; computer simulation; hysteresis band comparator; load power factor correction; multilayer perceptron feedforward network; neural network technologies; power system current harmonics; power system voltage harmonics; pulse width modulation control; reference compensation currents estimation;
Journal_Title :
Electric Power Applications, IEE Proceedings -
DOI :
10.1049/ip-epa:20030009