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High-Efficient Direct Power Control Scheme Using Predictive Virtual Flux for Three-Phase Active Rectifiers

Authors :
Mihn Hoang Nguyen
Sangshin Kwak
Seungdeog Choi
Source :
Machines, Vol 12, Iss 5, p 290 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

In recent years, the pulse-width-modulation (PWM) converter has been found to have extensive applications in renewable energy, industrial fields, and others. The high efficiency requirement is crucial to operating a PWM rectifier in various applications, in addition to the fundamental control objectives of sinusoidal grid currents and the correct DC bus voltage. Additionally, in practical application, another issue arises when the grid voltage frequently experiences distortion, leading to a distorted grid current and a significant rise in total harmonic distortion (THD). To resolve these problems, a model predictive virtual flux-based direct power control (MPVFDPC) with improved power loss performance is proposed based on an integrated switching state predetermination strategy. The proposed MPVFDPC for PWM rectifier inherits the merits of both virtual flux control and direct power control, which have fast dynamic performance and the grid current THD is considerably decreased under distorted grid voltage states. The proposed technique aims to minimize switching loss under ideal and distorted grid voltage states by exploiting the discontinuous modulation concept by using a switching state predetermination strategy. The MPVFDPC with switching state predetermination strategy is proven by employing it in experiments as well as simulations in comparison with previous models: predictive direct power control (Conv. MPDPC) and conventional MPVFDPC (Conv. MPVFDPC). The acquired waveforms and quantitative data are employed to prove the effectiveness of the developed algorithm.

Details

Language :
English
ISSN :
20751702
Volume :
12
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Machines
Publication Type :
Academic Journal
Accession number :
edsdoj.9ebd9a1aba84ba0a8eddb0d25da624f
Document Type :
article
Full Text :
https://doi.org/10.3390/machines12050290