Skip to main content

Research Repository

Advanced Search

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

Garcia, Pablo; Blanco, Cristian; Navarro-Rodríguez, Ángel; Sumner, Mark

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


Authors

Pablo Garcia

Cristian Blanco

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 extractor that allows to isolate the harmonic components of both voltages and currents needed for the control of grid-tied converters. The proposed method is based on a modification of the Sliding Goertzel Transformation (SGT) that allows to include a predictive behavior with a prediction horizon equal to the processing window needed for the algorithm. The technique performance is compared with the well-established DSOGI alternative, allowing for a higher bandwidth in the estimation as well as improved immunity to changes in the magnitude, frequency and phase of the tracked signals. Additionally, the impact of the proposed method on the closed-loop performance of the current controlled converter is proposed as a metric, thus enabling other researches to have a clear view about the expected real impact of the different existing methods.

Citation

Garcia, P., Blanco, C., Navarro-Rodríguez, Á., & Sumner, M. (2017). Predictive frequency-based sequence estimator for control of grid-tied converters under highly distorted conditions. In 2017 IEEE Energy Conversion Congress and Exposition (ECCE) (2940-2947). https://doi.org/10.1109/ECCE.2017.8096542

Conference Name 2017 IEEE Energy Conversion Congress and Exposition (ECCE)
Conference Location Cincinnati, OH, USA
Start Date Oct 1, 2017
End Date Oct 5, 2017
Acceptance Date May 1, 2017
Online Publication Date Nov 7, 2017
Publication Date 2017
Deposit Date Mar 19, 2018
Publicly Available Date Mar 19, 2018
Peer Reviewed Peer Reviewed
Pages 2940-2947
Book Title 2017 IEEE Energy Conversion Congress and Exposition (ECCE)
ISBN 978-1-5090-2999-0
DOI https://doi.org/10.1109/ECCE.2017.8096542
Public URL https://nottingham-repository.worktribe.com/output/885171
Publisher URL http://ieeexplore.ieee.org/document/8096542/

Files





You might also like



Downloadable Citations