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

Blanco, Cristian, Garcia, Pablo, Navarro-Rodríguez, Ángel and Sumner, M. (2018) Predictive frequency-based sequence estimator for control of grid-tied converters under highly distorted conditions. IEEE Transactions on Industry Applications . ISSN 1939-9367

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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.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/937948
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.
Schools/Departments: University of Nottingham, UK > Faculty of Engineering > Department of Electrical and Electronic Engineering
Identification Number: https://doi.org/10.1109/TIA.2018.2846552
Depositing User: Burns, Rebecca
Date Deposited: 14 Jun 2018 09:55
Last Modified: 04 May 2020 19:40
URI: https://eprints.nottingham.ac.uk/id/eprint/52368

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