Artificial neural network-based power quality compensator

Abstract

A reliable and efficient adaptive neural network-based active power filter to estimate and compensate harmonic distortion from supply mains is presented in this paper. Nowadays, there is drastic rise of current and voltage harmonics in power systems, caused by nonlinear loads. Active power filters (APF) are used to mitigate harmonics and thereby, improve power quality. This paper deals with application of artificial neural network in shunt active power filter which provides ease in implementation and fast dynamic response compared to conventional active power filters. In depth analysis of neural network applications in the intelligent control and estimation for power quality compensation is presented in this paper. Here, both reference compensating current generation scheme as well as current controller for the active power filter are developed using artificial neural network technique. Effective compensation provided by the proposed artificial neural network-based shunt active power filter is proved through simulation results. Experimental analysis carried out using dSPACE DS1104 also validates power quality improvement by the proposed APF scheme.