Improved direct model predictive control for grid-connected power converters
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Fecha
2020-05
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Idioma
es
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MDPI AG
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Licencia CC
Atribución 4.0 Internacional (CC BY 4.0)
Licencia CC
https://creativecommons.org/licenses/by/4.0/deed.es
Resumen
This paper proposes a computationally efficient and robust direct model predictive control (DMPC) technique with enhanced steady-state performance for power converters tied to the electric utility. The discrete space vector modulation (DSVM) method is considered in the design of the suggested DMPC, where virtual voltage vectors (VVs) besides the real ones are utilized for improving the steady-state response of the proposed controller. Furthermore, for averting the high computational burden and making the proposed control technique simple, a deadbeat (DB) function is employed for calculating the reference VV based on the required reference current. Subsequently, a discrete-time integral term is combined with this DB function to enhance the robustness of the suggested DMPC technique against variations of the model parameters. Finally, the best virtual or real VV is chosen by a certain quality function, which will be applied to the power converter in the next sample. The suggested technique is verified by simulation results and its performance is compared with the classical DMPC and voltage-oriented control (VOC). © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license .
(http://creativecommons.org/licenses/by/4.0/).
Notas
Indexación: Scopus
Palabras clave
Advanced control., Robust control., Predictive control., Power converter., Deadbeat
Citación
Energies Volume 13, Issue 10May 2020 Article number 2597
DOI
10.3390/en13102597