This paper presents a long-horizon direct model predictive control for a series-connected modular rectifier. The topology combines a diode rectifier and an active-front-end (AFE) converter to achieve a modular dc railway power supply. Two formulations of the optimization problem, i.e., power and current control, are investigated. The current control problem-solved with the sphere decoder for reduced computational effort-is compared with the power control problem-solved with exhaustive enumeration-in terms of current distortions and distribution of the harmonic spectrum. The latter have to meet strict grid standards, such as IEEE 519 and IEC 61000-2-4 standards. As shown, thanks to the long prediction horizon the total demand distortion of the converter current can be reduced, while keeping the device switching frequency low due to the medium voltage target.

Long-horizon direct model predictive control for a series-connected modular rectifier

Rossi M.;Castelli Dezza F.;
2020

Abstract

This paper presents a long-horizon direct model predictive control for a series-connected modular rectifier. The topology combines a diode rectifier and an active-front-end (AFE) converter to achieve a modular dc railway power supply. Two formulations of the optimization problem, i.e., power and current control, are investigated. The current control problem-solved with the sphere decoder for reduced computational effort-is compared with the power control problem-solved with exhaustive enumeration-in terms of current distortions and distribution of the harmonic spectrum. The latter have to meet strict grid standards, such as IEEE 519 and IEC 61000-2-4 standards. As shown, thanks to the long prediction horizon the total demand distortion of the converter current can be reduced, while keeping the device switching frequency low due to the medium voltage target.
PCIM Europe Conference Proceedings
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1163834
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