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22-04-2023 | Original Paper

An improved low-computation model predictive direct power control strategy for three-level four-leg active power filter

Authors: Guifeng Wang, Jinxing Guo, Zhan Liu

Published in: Electrical Engineering | Issue 4/2023

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Abstract

Model predictive direct power control (MPDPC) strategy offers numerous benefits over the traditional control strategies in active power filters (APF). However, the real-time execution duration (RTED) reduction of model predictive control in multilevel inverters is a big challenge. In this paper, an improved low-computation model predictive direct power control strategy for three-level four-leg APF (TL-FL-APF) is presented. First, based on generalized instantaneous reactive power theory, a new predictive power model for TL-FL-APF is established. Then, in order to reduce the RTED, classical multiple power predictions are converted into single voltage prediction through the principle of deadbeat control, and the optimized vector range is reduced from 81 to 4–18 by the method of spatial stratification using the γ-component of reference voltage vector. Finally, the simulation and experimental results demonstrate that the proposed low-computation MPDPC has excellent performance.

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Metadata
Title
An improved low-computation model predictive direct power control strategy for three-level four-leg active power filter
Authors
Guifeng Wang
Jinxing Guo
Zhan Liu
Publication date
22-04-2023
Publisher
Springer Berlin Heidelberg
Published in
Electrical Engineering / Issue 4/2023
Print ISSN: 0948-7921
Electronic ISSN: 1432-0487
DOI
https://doi.org/10.1007/s00202-023-01818-2

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