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author:

Liao, Huangzheng (Liao, Huangzheng.) [1] | Jin, Tao (Jin, Tao.) [2] (Scholars:金涛) | Mon-Nzongo, Daniel Legrand (Mon-Nzongo, Daniel Legrand.) [3] | Tang, Jinquan (Tang, Jinquan.) [4] | Liu, Ziqiang (Liu, Ziqiang.) [5]

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EI

Abstract:

Based on the topology of five level nested neutral point clamped (NNPC) grid connected inverter, this paper compares two type of finite control set model predictive control (FCS-MPC) methods to reduce the amount of calculation time compare with the traditional FCS-MPC. The first method is based on space vector modulation approach which uses 60-degree voltage state vector for the prediction to reduce the calculation time of each control period in FCS-MPC algorithm. While the second method is to simplify the calculation time by using the FCS-MPC based on adjacent state vector method. Through comparative analysis, it can be seen that the 60 degrees sector FCS-MPC have similar performances regarding the current THD; the upper and lower DC voltage deviation of DC-link capacitors. The main difference is on the computation time which results to 35 control periods compare to 125 for the traditional FCS-MPC. The adjacent state vector method results to 7-29 control period. © 2021 IEEE.

Keyword:

Electric inverters Model predictive control Predictive control systems Topology Vectors Vector spaces

Community:

  • [ 1 ] [Liao, Huangzheng]Fuzhou University Fujian Key Laboratory of New Energy Generation and Power Conversion, College of Electrical Engineering and Automation, Fuzhou, China
  • [ 2 ] [Jin, Tao]Fuzhou University Fujian Key Laboratory of New Energy Generation and Power Conversion, College of Electrical Engineering and Automation, Fuzhou, China
  • [ 3 ] [Mon-Nzongo, Daniel Legrand]Fuzhou University Fujian Key Laboratory of New Energy Generation and Power Conversion, College of Electrical Engineering and Automation, Fuzhou, China
  • [ 4 ] [Tang, Jinquan]Research and Development, Department of Pearl Electric Corporation, Guangzhou, China
  • [ 5 ] [Liu, Ziqiang]Fuzhou University Fujian Key Laboratory of New Energy Generation and Power Conversion, College of Electrical Engineering and Automation, Fuzhou, China

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Year: 2021

Page: 173-177

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 4

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