TY - GEN
T1 - Long-horizon direct model predictive control for a series-connected modular rectifier
AU - Rossi, Mattia
AU - Liegmann, Eyke
AU - Karamanakos, Petros
AU - Castelli-Dezza, Francesco
AU - Kennel, Ralph
N1 - Publisher Copyright:
© VDE VERLAG GMBH · Berlin · Offenbach.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85089693215&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85089693215
SN - 9783800752454
T3 - PCIM Europe Conference Proceedings
SP - 342
EP - 349
BT - PCIM Europe-International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, 2020
PB - Mesago PCIM GmbH
T2 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Europe 2020
Y2 - 7 July 2020 through 8 July 2020
ER -