Multiple-vector direct model predictive control for grid-connected power converters with reduced calculation burden

Mohamed Abdelrahem, Faris Hamadto, Anath Garikapati, Ralph Kennel, Jose Rodriguez

Resultado de la investigación: Conference contribution

Resumen

This paper proposes a multiple-vector direct model predictive control (MV-DMPC) scheme with reduced calculation burden for grid-connected power converters. The proposed control scheme is based on the discrete space vector modulation (DSVM) technique, where the real voltage vectors (VVs) of the converter are employed together with new virtual VVs to improve the steady-state performance of the proposed controller. Furthermore, in order to reduce the calculation burden of the proposed strategy, a deadbeat function is presented to directly compute the reference voltage vector from the demanded reference current/power. Then, the optimal real or virtual voltage vector is selected based on a certain cost function to apply in the next sampling instant. The performance of the proposed method is validated via simulation results and compared with that of the conventional DMPC and the well-known voltage oriented control (VOC) with proportional-integral (PI) controllers.

Idioma originalEnglish
Título de la publicación alojadaProceedings - PRECEDE 2019
Subtítulo de la publicación alojada2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781538694145
DOI
EstadoPublished - 1 may 2019
Evento2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2019 - Quanzhou, China
Duración: 31 may 20192 jun 2019

Serie de la publicación

NombreProceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics

Conference

Conference2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2019
PaísChina
CiudadQuanzhou
Período31/05/192/06/19

Huella dactilar

Power Converter
Model predictive control
Model Predictive Control
Power converters
Voltage
Grid
Electric potential
Space Vector Modulation
Controller
Controllers
Vector spaces
Converter
Instant
Cost functions
Cost Function
Directly proportional
Modulation
Sampling
Simulation

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Control and Optimization

Citar esto

Abdelrahem, M., Hamadto, F., Garikapati, A., Kennel, R., & Rodriguez, J. (2019). Multiple-vector direct model predictive control for grid-connected power converters with reduced calculation burden. En Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics [8753253] (Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PRECEDE.2019.8753253
Abdelrahem, Mohamed ; Hamadto, Faris ; Garikapati, Anath ; Kennel, Ralph ; Rodriguez, Jose. / Multiple-vector direct model predictive control for grid-connected power converters with reduced calculation burden. Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics. Institute of Electrical and Electronics Engineers Inc., 2019. (Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics).
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abstract = "This paper proposes a multiple-vector direct model predictive control (MV-DMPC) scheme with reduced calculation burden for grid-connected power converters. The proposed control scheme is based on the discrete space vector modulation (DSVM) technique, where the real voltage vectors (VVs) of the converter are employed together with new virtual VVs to improve the steady-state performance of the proposed controller. Furthermore, in order to reduce the calculation burden of the proposed strategy, a deadbeat function is presented to directly compute the reference voltage vector from the demanded reference current/power. Then, the optimal real or virtual voltage vector is selected based on a certain cost function to apply in the next sampling instant. The performance of the proposed method is validated via simulation results and compared with that of the conventional DMPC and the well-known voltage oriented control (VOC) with proportional-integral (PI) controllers.",
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Abdelrahem, M, Hamadto, F, Garikapati, A, Kennel, R & Rodriguez, J 2019, Multiple-vector direct model predictive control for grid-connected power converters with reduced calculation burden. En Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics., 8753253, Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2019, Quanzhou, China, 31/05/19. https://doi.org/10.1109/PRECEDE.2019.8753253

Multiple-vector direct model predictive control for grid-connected power converters with reduced calculation burden. / Abdelrahem, Mohamed; Hamadto, Faris; Garikapati, Anath; Kennel, Ralph; Rodriguez, Jose.

Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics. Institute of Electrical and Electronics Engineers Inc., 2019. 8753253 (Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics).

Resultado de la investigación: Conference contribution

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T1 - Multiple-vector direct model predictive control for grid-connected power converters with reduced calculation burden

AU - Abdelrahem, Mohamed

AU - Hamadto, Faris

AU - Garikapati, Anath

AU - Kennel, Ralph

AU - Rodriguez, Jose

PY - 2019/5/1

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N2 - This paper proposes a multiple-vector direct model predictive control (MV-DMPC) scheme with reduced calculation burden for grid-connected power converters. The proposed control scheme is based on the discrete space vector modulation (DSVM) technique, where the real voltage vectors (VVs) of the converter are employed together with new virtual VVs to improve the steady-state performance of the proposed controller. Furthermore, in order to reduce the calculation burden of the proposed strategy, a deadbeat function is presented to directly compute the reference voltage vector from the demanded reference current/power. Then, the optimal real or virtual voltage vector is selected based on a certain cost function to apply in the next sampling instant. The performance of the proposed method is validated via simulation results and compared with that of the conventional DMPC and the well-known voltage oriented control (VOC) with proportional-integral (PI) controllers.

AB - This paper proposes a multiple-vector direct model predictive control (MV-DMPC) scheme with reduced calculation burden for grid-connected power converters. The proposed control scheme is based on the discrete space vector modulation (DSVM) technique, where the real voltage vectors (VVs) of the converter are employed together with new virtual VVs to improve the steady-state performance of the proposed controller. Furthermore, in order to reduce the calculation burden of the proposed strategy, a deadbeat function is presented to directly compute the reference voltage vector from the demanded reference current/power. Then, the optimal real or virtual voltage vector is selected based on a certain cost function to apply in the next sampling instant. The performance of the proposed method is validated via simulation results and compared with that of the conventional DMPC and the well-known voltage oriented control (VOC) with proportional-integral (PI) controllers.

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Abdelrahem M, Hamadto F, Garikapati A, Kennel R, Rodriguez J. Multiple-vector direct model predictive control for grid-connected power converters with reduced calculation burden. En Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics. Institute of Electrical and Electronics Engineers Inc. 2019. 8753253. (Proceedings - PRECEDE 2019: 2019 IEEE International Symposium on Predictive Control of Electrical Drives and Power Electronics). https://doi.org/10.1109/PRECEDE.2019.8753253