Model Predictive Control of High-Power Modular Multilevel Converters - An Overview

Apparao Dekka, Bin Wu, Venkata Yaramasu, Ricardo Lizana Fuentes, Navid R. Zargari

Research output: Contribution to journalArticlepeer-review

100 Scopus citations

Abstract

Model predictive control (MPC) has emerged as a promising approach to control a modular multilevel converter (MMC). With the help of a cost function, the control objectives of an MMC are achieved easily by using an MPC approach. However, the MPC has several technical challenges and issues including the need of accurate system models, computational complexity, and variable switching frequency operation and weighting factor selection, when it comes to the control of an MMC. In the past few years, several research studies are conducted to address some of the challenges and issues in an MPC and developed several model predictive algorithms for an MMC. In this paper, the importance of each challenge and its impact on the system performance is discussed. Also, the MMC mathematical models used in the implementation of MPC are presented. Furthermore, some of the popular MPC algorithms are discussed briefly, and their features and performance are highlighted through case studies. Finally, summary and future trends of MPC for an MMC are presented.

Original languageEnglish (US)
Article number8529274
Pages (from-to)168-183
Number of pages16
JournalIEEE Journal of Emerging and Selected Topics in Power Electronics
Volume7
Issue number1
DOIs
StatePublished - Mar 2019

Keywords

  • Capacitor voltage control
  • circulating current (CC)
  • common-mode voltage (CMV)
  • dc-link current ripple
  • model predictive control (MPC)
  • modular multilevel converter (MMC)

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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