Model Predictive Control for Modular Multilevel ACAC Converters with Modulated Models

PROJECT TITLE :

Modulated Model Predictive Control for Modular Multilevel ACAC Converter

ABSTRACT:

Due to its appealing properties, the modular multilevel converter (MMC) is highly common in high power applications. The full bridge-based MMC with direct ac/ac conversion from three-phase to single-phase is a viable option for ac power supply (ACPS). Modified model predictive control (MMPC) approaches for MMC-ACPS have been suggested in this research to increase steady-state multi-objective tracking performance. First, output voltage levels from the upper and lower arms are combined and represented by vectors in the current increments plane. Then, the vectors in the current increments plane are modulated to represent the combined voltage levels. Input and circulating current error predictions are used to partition the plane into eight sections. Modified vector sequences are used to eliminate these current tracking faults simultaneously at the end of each control period after determining sectors. Multiple current tracking errors are minimised by calculating the duty cycles of three selected vectors. The proposed MMPC makes extensive use of vector selection algorithms that have been optimised. In the proposed approaches, just the nearest nine vectors are used, thus the calculation amount is adequate and the dv/dt of the output voltage is likewise restricted. Experimental results show that the proposed control approaches function well in both steady state and dynamic conditions..

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