Finite-Set Model Predictive Control for 17-Level Inverter with Reduced Number of Iterations in Photovoltaic Applications

Mohamed Abdelrahem; Ibrahim Harbi; Mostafa Ahmed; M. Saad Bin Arif; Ralph Kennel; Jose Rodriguez

doi:10.1109/PRECEDE57319.2023.10174509

Finite-Set Model Predictive Control for 17-Level Inverter with Reduced Number of Iterations in Photovoltaic Applications

Mohamed Abdelrahem
, Ibrahim Harbi
, Mostafa Ahmed
, M. Saad Bin Arif
, Ralph Kennel
, Jose Rodriguez

Chair of High-Power Converter Systems

Faculty of Engineering
Technical University of Munich
Aligarh Muslim University
Universidad San Sebastian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Finite-set model predictive control (FS-MPC) algorithms provide excellent dynamic performance for the power electronics converters with the ability to easily include any non-linearities and constraints. However, the high number of iterations required for prediction and cost function evaluation, especially for multi-level converters, hampers the implementation of the FS-MPC techniques. In this paper, firstly, the deadbeat concept is utilized to directly obtain the reference voltage vector. Accordingly, the iterations required for prediction are eliminated. Secondly, the number of iterations for cost function evaluation is also reduced by selecting a certain number of voltage vectors based on the value of the reference voltage vector. Finally, experimental results using hardware in the loop (HIL) technology are given to validate the proposed FS-MPC technique.

Original language	English
Title of host publication	2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350396867
DOIs	https://doi.org/10.1109/PRECEDE57319.2023.10174509
State	Published - 2023
Event	2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023 - Wuhan, China Duration: 16 Jun 2023 → 19 Jun 2023

Publication series

Name	2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023

Conference

Conference	2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023
Country/Territory	China
City	Wuhan
Period	16/06/23 → 19/06/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

cost function
deadbeat
model predictive control
multi-level converters

Access to Document

10.1109/PRECEDE57319.2023.10174509

Cite this

Abdelrahem, M., Harbi, I., Ahmed, M., Arif, M. S. B., Kennel, R., & Rodriguez, J. (2023). Finite-Set Model Predictive Control for 17-Level Inverter with Reduced Number of Iterations in Photovoltaic Applications. In 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023 (2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PRECEDE57319.2023.10174509

Abdelrahem, Mohamed ; Harbi, Ibrahim ; Ahmed, Mostafa et al. / Finite-Set Model Predictive Control for 17-Level Inverter with Reduced Number of Iterations in Photovoltaic Applications. 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023).

@inproceedings{6eb8260de69b47b1bb6d8739c339ae2a,

title = "Finite-Set Model Predictive Control for 17-Level Inverter with Reduced Number of Iterations in Photovoltaic Applications",

abstract = "Finite-set model predictive control (FS-MPC) algorithms provide excellent dynamic performance for the power electronics converters with the ability to easily include any non-linearities and constraints. However, the high number of iterations required for prediction and cost function evaluation, especially for multi-level converters, hampers the implementation of the FS-MPC techniques. In this paper, firstly, the deadbeat concept is utilized to directly obtain the reference voltage vector. Accordingly, the iterations required for prediction are eliminated. Secondly, the number of iterations for cost function evaluation is also reduced by selecting a certain number of voltage vectors based on the value of the reference voltage vector. Finally, experimental results using hardware in the loop (HIL) technology are given to validate the proposed FS-MPC technique.",

keywords = "cost function, deadbeat, model predictive control, multi-level converters",

author = "Mohamed Abdelrahem and Ibrahim Harbi and Mostafa Ahmed and Arif, \{M. Saad Bin\} and Ralph Kennel and Jose Rodriguez",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023 ; Conference date: 16-06-2023 Through 19-06-2023",

year = "2023",

doi = "10.1109/PRECEDE57319.2023.10174509",

language = "English",

series = "2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023",

}

Abdelrahem, M, Harbi, I, Ahmed, M, Arif, MSB, Kennel, R & Rodriguez, J 2023, Finite-Set Model Predictive Control for 17-Level Inverter with Reduced Number of Iterations in Photovoltaic Applications. in 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023. 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023, Wuhan, China, 16/06/23. https://doi.org/10.1109/PRECEDE57319.2023.10174509

Finite-Set Model Predictive Control for 17-Level Inverter with Reduced Number of Iterations in Photovoltaic Applications. / Abdelrahem, Mohamed; Harbi, Ibrahim; Ahmed, Mostafa et al.
2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Finite-Set Model Predictive Control for 17-Level Inverter with Reduced Number of Iterations in Photovoltaic Applications

AU - Abdelrahem, Mohamed

AU - Harbi, Ibrahim

AU - Ahmed, Mostafa

AU - Arif, M. Saad Bin

AU - Kennel, Ralph

AU - Rodriguez, Jose

PY - 2023

Y1 - 2023

N2 - Finite-set model predictive control (FS-MPC) algorithms provide excellent dynamic performance for the power electronics converters with the ability to easily include any non-linearities and constraints. However, the high number of iterations required for prediction and cost function evaluation, especially for multi-level converters, hampers the implementation of the FS-MPC techniques. In this paper, firstly, the deadbeat concept is utilized to directly obtain the reference voltage vector. Accordingly, the iterations required for prediction are eliminated. Secondly, the number of iterations for cost function evaluation is also reduced by selecting a certain number of voltage vectors based on the value of the reference voltage vector. Finally, experimental results using hardware in the loop (HIL) technology are given to validate the proposed FS-MPC technique.

AB - Finite-set model predictive control (FS-MPC) algorithms provide excellent dynamic performance for the power electronics converters with the ability to easily include any non-linearities and constraints. However, the high number of iterations required for prediction and cost function evaluation, especially for multi-level converters, hampers the implementation of the FS-MPC techniques. In this paper, firstly, the deadbeat concept is utilized to directly obtain the reference voltage vector. Accordingly, the iterations required for prediction are eliminated. Secondly, the number of iterations for cost function evaluation is also reduced by selecting a certain number of voltage vectors based on the value of the reference voltage vector. Finally, experimental results using hardware in the loop (HIL) technology are given to validate the proposed FS-MPC technique.

KW - cost function

KW - deadbeat

KW - model predictive control

KW - multi-level converters

UR - https://www.scopus.com/pages/publications/85166220648

U2 - 10.1109/PRECEDE57319.2023.10174509

DO - 10.1109/PRECEDE57319.2023.10174509

M3 - Conference contribution

AN - SCOPUS:85166220648

T3 - 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023

BT - 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023

Y2 - 16 June 2023 through 19 June 2023

ER -

Abdelrahem M, Harbi I, Ahmed M, Arif MSB, Kennel R, Rodriguez J. Finite-Set Model Predictive Control for 17-Level Inverter with Reduced Number of Iterations in Photovoltaic Applications. In 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023). doi: 10.1109/PRECEDE57319.2023.10174509

Finite-Set Model Predictive Control for 17-Level Inverter with Reduced Number of Iterations in Photovoltaic Applications

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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