access icon free Integrated model predictive control with reduced switching frequency for modular multilevel converters

The indirect model predictive control (I-MPC) is one of the reduced computational predictive strategies, used to control the modular multilevel converter (MMC). This approach operates at higher switching frequency, which is not desirable for high-power applications. This study proposes an integrated solution for MMC by combining predictive control with the classical energy balancing approach. To implement the predictive algorithm, a detailed three-phase MMC model is presented. The three-phase model includes the zero sequence voltage to reduce the switching frequency of submodules. In addition, the output power quality is enhanced, while operating at reduced switching frequency. The performance of integrated approach is experimentally validated on a laboratory prototype under balanced and unbalanced conditions. In addition, the performance of integrated approach is compared with the existing methodology in terms of output current ripple, switching frequency, computational complexity, and total harmonic distortion.

Inspec keywords: harmonic distortion; power convertors; power supply quality; predictive control; frequency control

Other keywords: integrated model predictive control; switching frequency reduction; indirect model predictive control; zero sequence voltage; three-phase MMC model; output power quality; output current ripple; I-MPC; reduced computational predictive strategies; total harmonic distortion; computational complexity; energy balancing approach; modular multilevel converters

Subjects: Frequency control; Power electronics, supply and supervisory circuits; Power convertors and power supplies to apparatus; Power supply quality and harmonics; Control of electric power systems; Optimal control

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      • 14. Gong, Z., Dai, P., Yuan, X., et al: ‘Design and experimental evaluation of fast model predictive control for modular multilevel converters’, IEEE Trans. Ind. Electron., 2015, PP, (99), pp. 11.
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http://iet.metastore.ingenta.com/content/journals/10.1049/iet-epa.2016.0454
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