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Predictive frequency-based sequence estimator for control of grid-tied converters under highly distorted conditions

Blanco, Cristian; Garcia, Pablo; Navarro-Rodríguez, Ángel; Sumner, M.

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Authors

Cristian Blanco

Pablo Garcia

Ángel Navarro-Rodríguez

MARK SUMNER MARK.SUMNER@NOTTINGHAM.AC.UK
Professor of Electrical Energy Systems



Abstract

This paper proposes a novel frequency-based predictive sequence estimator that allows for the isolation of voltages and currents harmonic components needed for the control of grid-tied converters. The proposed method relays on an enhanced Sliding Goertzel Transformation (SGT) by adding a predictive estimator with a prediction horizon equal to the SGT processing window. The performance of the proposed method is compared with the well-established DSOGI alternative, proving a higher estimation bandwidth as well as improved immunity to changes in the magnitude, frequency and phase of the tracked signals. Additionally, the close-loop performance in a current-controlled grid-tied inverter using the proposed sequence extractor is analyzed. The presented results allow to quantitatively measure the estimator impact over the power converter performance in a real application.

Journal Article Type Article
Acceptance Date May 27, 2018
Online Publication Date Jun 12, 2018
Publication Date Oct 31, 2018
Deposit Date Jun 14, 2018
Publicly Available Date Jun 14, 2018
Journal IEEE Transactions on Industry Applications
Print ISSN 0093-9994
Electronic ISSN 1939-9367
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 54
Issue 5
Pages 5306-5317
DOI https://doi.org/10.1109/TIA.2018.2846552
Public URL https://nottingham-repository.worktribe.com/output/937948
Publisher URL https://ieeexplore.ieee.org/document/8382289/
Additional Information © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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