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

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

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, October). Predictive frequency-based sequence estimator for control of grid-tied converters under highly distorted conditions. Presented at 2017 IEEE Energy Conversion Congress and Exposition (ECCE), Cincinnati, OH, USA

• Presentation Conference Type: Edited Proceedings
• Conference Name: 2017 IEEE Energy Conversion Congress and Exposition (ECCE)
• 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/
• Contract Date: Mar 19, 2018