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Priority Sorting Approach for Modular Multilevel Converter Based on Simplified Model Predictive Control

delete2018-06-01
delete128
PRE
AI
黄
黄家豪 (Jingjing Huang)
B
Bo Yang
F
Fanghong Guo
Z
Zaifu Wang
X
Xiangqian Tong
A
Aimin Zhang *
J
Jianfang Xiao
DOI:10.1109/TIE.2017.2774725delete
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摘要

摘要

En 中文
In this paper, a priority sorting approach based on simplified model predictive control (MPC) is proposed for modular multilevel converter (MMC). It aims at reducing the computational burden of conventional MPC method while maintaining the system performance, especially under high voltage levels. The proposed approach mainly consists of three parts, i.e., grid-side current control (GCC), circulating current control (CCC), and capacitor voltage balancing control (CVBC). The GCC and CCC are separately designed with simplified MPCs, avoiding the weight factor. Meanwhile, the redundant calculations are eliminated in GCC by considering the desired predicted output voltage of equivalent MMC model. To further minimize the optional combinations of the switching states, the CCC is constructed by utilizing the output of GCC and the arm current. Besides, a novel priority sorting approach is proposed for the CVBC to alleviate the sorting operation. The submodules are divided into three groups according to the detected capacitor voltages. Moreover, the groups are assigned with different priorities based on the arm current, and only one group needs the sorting process. Additionally, a reduced frequency approach is introduced to decrease the power loss in the steady state. The effectiveness of the proposed approach is validated by both simulation and experimental results.
Keyword:
Circulating current
model predictive control (MPC)
modular multilevel converter (MMC)
voltage balancing control
weight factor
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期刊

IEEE Transactions on Industrial Electronics 封面图
IEEE Transactions on Industrial Electronics
IF:
7.2
论文数:
1.8W
被引数:
9.8W

机构

X
xi'an jiaotong university
学者数:
9.3W
论文数: 6.7W
被引数: 75
N
Nanyang Technological University
学者数:
4.9W
论文数: 4.8W
被引数: 8.1W
A
agency for science technology & research (a*star)
学者数:
2.2W
论文数: 1.9W
被引数: 57
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