Model predictive current control of asymmetrical hybrid cascaded multilevel inverter

Han, Jingang; Zhao, Pinxuan; Yao, Gang; Chen, Hao; Wang, Yide; Benbouzid, Mohamed; Tang, Tianhao

doi:10.1007/s43236-022-00389-y

Cited by 4 publications

(2 citation statements)

References 33 publications

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“…As mentioned earlier, MPC can facilitate the optimal control of the multi-objective terms/parameters in a predictive cost function. Several of these parameters might have equal control priorities [68][69][70][71], which is ideal for symmetrical cost function designs. However, other control objectives may have differing priorities, e.g., torque and flux control in electrical machine drives.…”

Section: Heuristic Weighting Factor Tuningmentioning

confidence: 99%

Weighting Factor Design Techniques for Predictive Control of Power Electronics and Motor Drives

Zhang

Babayomi

et al. 2023

Symmetry

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The rapid growth of energy demand requires progressive energy generation. This, together with the demand for higher efficiency and flexibility, has promoted the application of power electronics in energy systems. During the past decade, model predictive control (MPC) of power electronics has witnessed significant advancements in both dynamic performance and optimal control of the multi-objective terms. Several of these terms can have equal control priorities, resulting in a symmetrical cost function; however, most objectives have different priorities and require weighting factors to resolve the asymmetry in the cost function. Currently, researchers continue to encounter challenges in the optimal design of weighting factors. Moreover, the relative performance of different techniques that either utilize or avoid the weighting factor are uncertain. Therefore, this study focuses on weighting factor design techniques in the literature as applied to wind/solar energy conversion, microgrids, grid-connected converters, and other high-performance converter-based systems. These are grouped under the heuristic, offline tuning, sequential, and online optimization methods. This study demonstrates that optimal online tuning of weighting factors and sequential MPC methods can both offer improved robustness against parameter uncertainties. In addition, the advantages and limitations of different techniques are highlighted.

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Section: Heuristic Weighting Factor Tuningmentioning

confidence: 99%

Weighting Factor Design Techniques for Predictive Control of Power Electronics and Motor Drives

Zhang

Babayomi

et al. 2023

Symmetry

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show abstract

“…The MPC approach in asymmetric systems is not discussed and few studies have been conducted with conventional methods [6]. So far, few analytical studies have been conducted on the MPC approach in the presence of power converters with asymmetric topology and switching [7], which require further studies to simplify and functionalize the MPC approach.…”

Section: Introductionmentioning

confidence: 99%

Review of Model Predictive Control of Distributed Energy Resources in Microgrids

et al. 2022

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In recent years, in response to increasing environmental concerns, advances in renewable energy technology and reduced costs have caused a significant increase in the penetration of distributed generation resources in distribution networks. Nonetheless, the connection of distributed generation resources to distribution networks has created new challenges in the control, operation, and management of network reliability. This article is a review on the model predictive control (MPC) for distributed energy resources (DER) in microgrids. The solutions of MPC for energy conversion of solar photovoltaic, wind, and energy storage systems are covered in detail. MPC’s applications for increasing reliability of grid-connected converters under (a)symmetrical grid faults are also discussed. The promising potentials of the applications of MPC to the stable multi-variable control performance of DERs are highlighted. This work reflects strong symmetry on MPC control strategies and provides guidance map for readers to facilitate future research works in these exciting fields.

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Model Predictive Current Control Strategy for Improved Dynamic Response in Cascaded H-Bridge Multilevel Inverters

Baek

Lee

2023

J. Electr. Eng. Technol.

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Model predictive current control of asymmetrical hybrid cascaded multilevel inverter

Cited by 4 publications

References 33 publications

Weighting Factor Design Techniques for Predictive Control of Power Electronics and Motor Drives

Weighting Factor Design Techniques for Predictive Control of Power Electronics and Motor Drives

Review of Model Predictive Control of Distributed Energy Resources in Microgrids

Model Predictive Current Control Strategy for Improved Dynamic Response in Cascaded H-Bridge Multilevel Inverters

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