Long-Horizon Direct Model Predictive Control for a Series-Connected Modular Rectifier

Conference: PCIM Europe digital days 2020 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management
07/07/2020 - 07/08/2020 at Deutschland

Proceedings: PCIM Europe digital days 2020

Pages: 8Language: englishTyp: PDF

Rossi, Mattia; Castelli-Dezza, Francesco (Politecnico di Milano, Milan, Italy)
Liegmann, Eyke; Kennel, Ralph (Technical University of Munich, Munich, Germany)
Karamanakos, Petros (Tampere University, Tampere, Finland)

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.