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

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

doi:10.1109/jestpe.2018.2880137

Cited by 184 publications

(85 citation statements)

References 98 publications

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“…The same previous steps are applicable to conclude the voltage reference final equation for the lower MMC arm of section x as presented in (24).…”

Section: Deadbeat Predictive Current Controlmentioning

confidence: 99%

“…On the other hand, a model predictive control for circulating current suppression is proposed in [23]. However, when increasing the number of SMs in an MMC, this leads to a higher number of switching states, which increases the control complexity due to the massive calculations that could overload the digital controller [24]. A new method for reducing the circulating current by adding second and fourth harmonics in the upper and the lower MMC arm currents is presented in [7].…”

Section: Introductionmentioning

confidence: 99%

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Deadbeat Predictive Current Control for Circulating Currents Reduction in a Modular Multilevel Converter Based Rail Power Conditioner

et al. 2020

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This paper presents a deadbeat predictive current control methodology to reduce the circulating currents in a modular multilevel converter (MMC) when it operates as a rail power conditioner (RPC) in a conventional railway system-based V/V connection. For this purpose, a half-bridge MMC based on half-bridge submodules, operating as an RPC is explained, and the total system is denominated as a simplified rail power conditioner (SRPC). The SRPC in this study is used to compensate harmonics, reactive power, and the negative sequence component of currents. This paper explains the SRPC system architecture, the key control algorithms, and the deadbeat predictive current control methodology. Mathematical analysis, based on the MMC equivalent circuit, is described and the reference equations are presented. Moreover, simulation results of the deadbeat predictive current control methodology are compared with the results of the conventional proportional-integral (PI) controller. This comparison is to verify the effectiveness of the proposed control strategy. Simulation results of the SRPC show reduced circulating currents in the MMC phases when using the predictive control approach, besides accomplishing power quality improvement at the three-phase power grid side.

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“…The same previous steps are applicable to conclude the voltage reference final equation for the lower MMC arm of section x as presented in (24).…”

Section: Deadbeat Predictive Current Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Deadbeat Predictive Current Control for Circulating Currents Reduction in a Modular Multilevel Converter Based Rail Power Conditioner

et al. 2020

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“…Due to the challenging control of MMC, which involves various control objectives such as the proper magnitude and frequency of output current, circulating current suppression, and capacitor voltage balancing, the MMC requires a proper and robust control scheme to achieve these control objectives. In recent years, the MPC is known as an advantageous approach to control the MMC, owing to numerous advantages such as capability in controlling multiple objectives simultaneously with a single cost function and superior dynamic performance [27]. Although the direct MPC is straightforward to implement, it suffers from a substantial computational burden due to 2 2N possible switching states when evaluating every sampling instant.…”

Section: Model Predictive Control For MMCmentioning

confidence: 99%

Switching Loss Balancing Technique for Modular Multilevel Converters Operated by Model Predictive Control Method

Nguyen

Kwak

2019

Electronics

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The sorting algorithm is the most widely accepted capacitor voltage balancing strategy for a modular multilevel converter. This strategy offers to keep the balance among submodule capacitor voltages under all of the modular multilevel converter working conditions. However, this method generates unnecessary switching transitions in submodules, which results in high switching frequency and switching loss, and uneven distribution of switching transitions and switching loss among submodules (SMs). In this paper, a simplified switching loss balancing control strategy was proposed in order to handle these issues. The proposed approach adjusted the submodule selection process of the sorting algorithm by taking into consideration the number of switching transitions in addition to the capacitor voltages. Even distribution of switching transitions and switching loss was achieved, and the average switching loss was reduced at the cost of slightly increasing the capacitor voltage fluctuations. The effectiveness of the proposed approach was verified through both simulation and experimental results.

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“…Among them, model predictive control (MPC) is an interesting control scheme for the MMC. Its advantages include straightforward implementation, fast dynamic response, and suitability for dealing with multiple objectives [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

A Reverse Model Predictive Control Strategy for a Modular Multilevel Converter

et al. 2019

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In recent years, modular multilevel converters (MMCs) have developed rapidly, and are widely used in medium and high voltage applications. Model predictive control (MPC) has attracted wide attention recently, and its advantages include straightforward implementation, fast dynamic response, simple system design, and easy handling of multiple objectives. The main technical challenge of the conventional MPC for MMC is the reduction of computational complexity of the cost function without the reduction of control performance of the system. Some modified MPC scan decrease the computational complexity by evaluating the number of on-state sub-modules (SMs) rather than the number of switching states. However, the computational complexity is still too high for an MMC with a huge number of SMs. A reverse MPC (R-MPC) strategy for MMC was proposed in this paper to further reduce the computational burden by calculating the number of inserted SMs directly, based on the reverse prediction of arm voltages. Thus, the computational burden was independent of the number of SMs in the arm. The control performance of the proposed R-MPC strategy was validated by Matlab/Simulink software and a down-scaled experimental prototype.

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

Cited by 184 publications

References 98 publications

Deadbeat Predictive Current Control for Circulating Currents Reduction in a Modular Multilevel Converter Based Rail Power Conditioner

Deadbeat Predictive Current Control for Circulating Currents Reduction in a Modular Multilevel Converter Based Rail Power Conditioner

Switching Loss Balancing Technique for Modular Multilevel Converters Operated by Model Predictive Control Method

A Reverse Model Predictive Control Strategy for a Modular Multilevel Converter

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