research article

Low Switching Frequency Multi-Layered Model Predictive Control Strategy for Three-Phase PWM Rectifier

Abstract

[Objective] With the continuous expansion of the use of DC microgrids in distribution networks, high-power three-phase pulse width modulation (PWM) rectifiers are becoming increasingly important. Compared with the two-level PWM rectifiers, three-phase three-level PWM rectifiers can significantly improve the withstand voltage and effective capacity of the devices while obtaining excellent grid side power quality, but their control objectives and complexity are greatly increased. The existing rectifier model predictive control algorithms have problems such as large amounts of calculation, difficulty in setting weight coefficients, and high switching frequency in multi-objective control of three-level PWM rectifiers. As a result, the rectifiers require high computing power from the controllers and have reduced performance, restricting their widespread use. [Method] To solve the above problems, this article took three-phase three-level high-power PWM rectifiers as the research object, improved the traditional model predictive control, and proposed a low switching frequency PWM rectifier multi-Layered model predictive control strategy based on current waveform similarity coefficient to achieve multi-objective optimization control of the three-phase three-level PWM rectifiers. A simulation and experimental platform was built for simulation and experimental verification. [Result] Simulation and experimental results show that this control strategy effectively reduces the amounts of calculation, achieves a lower current distortion rate at a lower switching frequency, and achieves effective control under multi-objective constraints. [Conclusion] This control strategy can be applied to the control of high-power PWM rectifiers to reduce system switching losses and improve system reliability

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