A three-phase four-leg inverter-based active power filter for unbalanced current compensation using a petri probabilistic fuzzy neural network

Kuang Hsiung Tan, Faa Jeng Lin, Jun Hao Chen

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13 Scopus citations

Abstract

A three-phase four-leg inverter-based shunt active power filter (APF) is proposed to compensate three-phase unbalanced currents under unbalanced load conditions in grid-connected operation in this study. Since a DC-link capacitor is required on the DC side of the APF to release or absorb the instantaneous apparent power, the regulation control of the DC-link voltage of the APF is important especially under load variation. In order to improve the regulation control of the DC-link voltage of the shunt APF under variation of three-phase unbalanced load and to compensate the three-phase unbalanced currents effectively, a novel Petri probabilistic fuzzy neural network (PPFNN) controller is proposed to replace the traditional proportional-integral (PI) controller in this study. Furthermore, the network structure and online learning algorithms of the proposed PPFNN are represented in detail. Finally, the effectiveness of the three-phase four-leg inverter-based shunt APF with the proposed PPFNN controller for the regulation of the DC-link voltage and compensation of the three-phase unbalanced current has been demonstrated by some experimental results.

Original languageEnglish
Article number2005
JournalEnergies
Volume10
Issue number12
DOIs
StatePublished - Dec 2017

Keywords

  • Active power filter
  • Petri probabilistic fuzzy neural network
  • Power quality
  • Three-phase four-leg inverter

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