An Optimal Control Set Model Predictive Control Method for Modular Multilevel Converters

Abstract

The present invention relates to an optimized control set model predictive control method for a modular multilevel converter, comprising: optimization of the insertion number and voltage fluctuation range of sub-modules based on the ideal voltage state of the modular multilevel converter, Determine the optimal control set of the submodule insertion number range, the submodule includes the upper bridge arm submodule and the lower bridge arm submodule; within the scope of the optimal control set, optimize through the model predictive control method to determine the optimal submodule Optimizing the number of insertions; according to the optimal number of insertions, the bridge arm voltage balance of the modular multilevel converter is realized and the PWM switching signal is generated to realize the model predictive control of the modular multilevel converter. Compared with the prior art, the present invention has the advantages of less search times, less calculation, and excellent static and dynamic control performance.

Description

Technical field [0001] The invention relates to the field of modular multi-level converter control, in particular to an optimized control set model predictive control method of a modular multi-level converter. Background technique [0002] Modular multilevel converter is a kind of converter with modular structure, easy cascading, low output voltage and current harmonics. Due to its advantages in loss, redundancy, switching frequency, etc., it is widely used in high-voltage and high-power engineering sites such as high-voltage direct current transmission, flexible power transmission, grid connection of wind farms, and medium and high-voltage electric drive. [0003] Since the bridge arms of the modular multilevel converter are connected in parallel at both ends of the DC bus, the sub-module capacitance is in a floating state, and the fluctuation of the sub-module capacitance voltage makes it difficult for the sum of the bridge arms to connect to the sub-module voltage to be consiste...

AI Technical Summary

Problems solved by technology

Existing literature mostly adopts the design of PI, PR or vector decoupling control methods to suppress the circulating current of modular multilevel converters. However, due to the large number of switch combinations and strong nonlinearity, the stability margin of traditional controllers is reduced, and the dynamic Poor performance, which limits the promotion of engineering applications

[0004] Model predictive control has been successfully applied in modular multilevel converters and has attracted widespread attention because of its intuitiveness, flexibility, strong robustness, and adaptability to nonlinear and multi-control objects. The existing model predictive control is often Firstly, the global optimization calculation is performed on the number of submodules that may be inserted into the upper and lower bridge arms, and then the bridge arm voltage balance of the modular multilevel converter is realized according to the determined number of inserted submodules in the upper and lower bridge arms, and PWM is generated. switch signal, so as to realize the model predictive control of the modular multilevel converter. Since this method needs to optimize the number of inserted sub-modules at the global level, the calculation amount is large and the calculation is complicated, which leads to poor engineering practicability. powerful

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