Finite-Set Model Predictive Control for a Hybrid Modular Multilevel Converter in a Microgrid

Hadis Hosseinpour, Tomislav Dragicevic, Mohammed Ben-Idris, Poria Fajri

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


With the rapid development of power electronic technology, modular multilevel converters (MMCs) are known as one of the applicable and effective typologies of voltage source converters (VSCs). However, the control of the MMCs is complicated and can be challenging due to the use of a large number of submodules. Also, using traditional controlling methods for the MMCs shows slow transient responses during faults. Model predictive control (MPC) has been proposed as a promising alternative to overcome this challenge. The MPC provides MMCs with controlling multiple objectives with a single cost function, improving the dynamic response. In this study, the MMC includes half-bridge and full-bridge submodules, which is refer to as a Hybrid MMC. An electrical vehicle charging station is considered as a source of harmonics used in this study. This paper develops a Hybrid MMC controlled by a discrete-time model predictive control, finite set MPC (FS-MPC), for a hybrid MMC. The result of comparing the FS-MPC performance with a PI controller shows the efficacy of the FS-MPC for harmonic reduction, fast transient responses, and circulating current mitigation.
Original languageEnglish
Title of host publicationProceedings of 2022 North American Power Symposium (NAPS)
Number of pages6
Publication date2023
ISBN (Electronic)978-1-6654-9921-7
Publication statusPublished - 2023
Event2022 North American Power Symposium - Salt Lake City, United States
Duration: 9 Oct 202211 Oct 2022


Conference2022 North American Power Symposium
Country/TerritoryUnited States
CitySalt Lake City
Series2022 North American Power Symposium, Naps 2022


  • Full-bridge submodule
  • Half-bridge submodule
  • Hybrid modular multilevel converters
  • Model predictive control


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