Computationally-Efficient Optimal Control of Cascaded Multilevel Inverters with Power Balance for Energy Storage Systems

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Abstract

This article proposes an optimal current control technique with switching event minimization for grid-interactive cascaded multilevel inverters (CMI) interfaced with battery energy storage sources. The proposed control scheme enables power-balancing functionality of battery cells, realizing optimal smart operation of CMI. Model predictive control (MPC) is known as a potential approach for multiobjective control schemes in single-loop manner for power electronics interfaces. However, MPC schemes are suffering from high computational burden that is magnified in topologies like the CMI, which have a substantial number of redundant control actions. The proposed control scheme utilizes a dynamic lookup matrix as an internal optimizer tool. The redundant switching sequences are cycled to equalize the power drawn from the independent battery energy storage sources while achieving a minimum energy control. The theoretical analysis and experimental case studies verify robustness and computational efficiency of the proposed multicriteria optimal controller with similar objective tracking when compared to finite-set MPC.

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APA

Easley, M., Shadmand, M. B., & Abu-Rub, H. (2021). Computationally-Efficient Optimal Control of Cascaded Multilevel Inverters with Power Balance for Energy Storage Systems. IEEE Transactions on Industrial Electronics, 68(12), 12285–12295. https://doi.org/10.1109/TIE.2020.3048281

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