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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-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 languageEnglish
Title of host publication2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350396867
DOIs
StatePublished - 2023
Event2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023 - Wuhan, China
Duration: 16 Jun 202319 Jun 2023

Publication series

Name2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023

Conference

Conference2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023
Country/TerritoryChina
CityWuhan
Period16/06/2319/06/23

Keywords

  • cost function
  • deadbeat
  • model predictive control
  • multi-level converters

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