Long-Horizon MPC Reference Generator for Circulating Currents in Modular Multilevel Converter-Based Variable-Speed Drives

The article introduces a circulating current reference generator based on a constrained model predictive control (MPC) in modular multilevel converters (M2C) for drive applications. It aims to control the energy in each cluster by generating optimal circulating currents over a long-horizon prediction while considering branch current limits. The optimal control problem is decomposed into smaller subproblems, which allows the utilization of an iterative algorithm based on the alternating direction method of multipliers (ADMM) to efficiently solve the optimization problem. As a result, the ADMM-based reference generator enables a considerably extended prediction horizon, which enhances M2C performance, particularly in balancing and mitigating low-frequency oscillations in capacitor voltages during challenging operating conditions like low-speed and high-torque scenarios. The proposed control is validated by experimental results using an M2C with four cells per cluster driving a 3 kW induction machine.

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Publication Details

Journal
IEEE Transactions on Industrial Electronics
Published
2025-02-03
DOI
https://doi.org/10.1109/tie.2025.3528493
Citations
4
Primary Topic
HVDC Systems and Fault Protection
Type
article
Field-Weighted Citation Impact
2.92
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article

Long-Horizon MPC Reference Generator for Circulating Currents in Modular Multilevel Converter-Based Variable-Speed Drives

Javier Pereda, Andrés Mora, Matías Correa, Sebastián Rivero
4 citations
IEEE Transactions on Industrial Electronics
HVDC Systems and Fault Protection
2.92
article

Long-Horizon MPC Reference Generator for Circulating Currents in Modular Multilevel Converter-Based Variable-Speed Drives

Javier Pereda, Andrés Mora, Matías Correa, Sebastián Rivero
article en
4 citations

Abstract

The article introduces a circulating current reference generator based on a constrained model predictive control (MPC) in modular multilevel converters (M2C) for drive applications. It aims to control the energy in each cluster by generating optimal circulating currents over a long-horizon prediction while considering branch current limits. The optimal control problem is decomposed into smaller subproblems, which allows the utilization of an iterative algorithm based on the alternating direction method of multipliers (ADMM) to efficiently solve the optimization problem. As a result, the ADMM-based reference generator enables a considerably extended prediction horizon, which enhances M2C performance, particularly in balancing and mitigating low-frequency oscillations in capacitor voltages during challenging operating conditions like low-speed and high-torque scenarios. The proposed control is validated by experimental results using an M2C with four cells per cluster driving a 3 kW induction machine.

IEEE Transactions on Industrial ElectronicsVol. 72(8)
Pontificia Universidad Católica de Chile (CL), Federico Santa María Technical University (CL)
Affordable and clean energy
Openalex Percentile: Top 10%
HVDC Systems and Fault Protection
2.92
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