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Modelling and design issues of model predictive current control of a voltage source converter
Author(s)
Suke, Penelope
Date Issued
2023
Type
Thesis
Publisher
Cape Peninsula University of Technology
Abstract
This research implements a Model Predictive Current Control scheme to monitor the output current for a three-phase, two-level VSC. A Finite State-Model Predictive Current Control technique will be presented for a three-phase, two-level VSC. Finite State Model Predictive Current Control proved to be a viable control method for power converters. One of several key benefits is the ability to monitor several system parameters with a single control rule by combining the system parameters with correct weighting factors. Nevertheless, these coefficients are determined through empirical calculations in the present leading-edge research. Thus far, no analytical or numerical method has been devised to obtain an ideal resolution. Furthermore, the empirical technique is not often concise, and no processes have already been identified. The whole research presents a method to a set of instructions that reduces the unpredictability of this process. Firstly, FS-MPCC will be introduced to decrease the computation effort for Model Predictive Current Control as well as to forecast future load current value for all eight generated potential switching states produced by the converter. secondly, this study classifies various cost functions and compares the performance of a system using delay compensation to a system without delay compensation. The objective is to assess the influence of delay compensation on the desired outcome and overall system performance. The various phases of the empiric process are then described. Lastly, the performance assessment of the FS-MPCC for a three-phase, two-level voltage source converter is reviewed in terms of power quality, dynamic performance, and tracking behavior. Modeling and simulation will be performed using the programs MATLAB / Simulink.
Additional information
Thesis (MEng (Energy))--Cape Peninsula University of Technology, 2023
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Suke_Penelope_215289536.pdf
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3.67 MB
Format
Adobe PDF
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