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A Model Predictive Control Method With Adaptive Weighting Factors for Enhancing Performance of Modular Multilevel Converters

Chengjun Tang, Torbjörn Thiringer

2024IEEE Journal of Emerging and Selected Topics in Power Electronics11 citationsDOI

Abstract

This article introduces an approach to enhance the performance of modular multilevel converters (MMCs) by utilizing the direct model predictive control (MPC) strategy. The novel MPC method presented here incorporates a dynamic cost function, which adapts weighting factors according to the varying submodule (SM) capacitor voltages in the MMC. Through thorough simulation and experimental analysis, it is evident that the proposed MPC technique improves the performance of the MMC operation across a range of modulation indices. In addition, the approach achieves the desired <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2N+1$ </tex-math></inline-formula> phase output voltage level, which reduces the total harmonics distortion (THD) in the output voltage and current. Furthermore, the MPC controller demonstrates robustness against potential errors in system parameter estimation through the simulation results.

Topics & Concepts

ConvertersWeightingModular designModel predictive controlControl theory (sociology)Computer scienceControl (management)Electronic engineeringControl engineeringEngineeringArtificial intelligenceElectrical engineeringPhysicsVoltageAcousticsOperating systemHVDC Systems and Fault ProtectionMultilevel Inverters and ConvertersMicrogrid Control and Optimization
A Model Predictive Control Method With Adaptive Weighting Factors for Enhancing Performance of Modular Multilevel Converters | Litcius