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Author:

Wang, Jinyu (Wang, Jinyu.) | Liu, Zhijie (Liu, Zhijie.) | Wang, Zhuodi (Wang, Zhuodi.) | Huang, Jingjing (Huang, Jingjing.) | Liu, Xiong (Liu, Xiong.)

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Abstract:

Because of many attractive merits, such as easy realization, excellent dynamic performance and multi-objective regulation capability, model predictive control (MPC) is widely utilized in voltage source converters (VSCs). However, when comes to modular multilevel converters (MMCs), it has several implementation challenges, such as heavy computation burden, non-fixed switching frequency, poor steady-state performance and complex weighting factor determination. Considering these challenges, this paper developed a novel modulated MPC method. With this method, the optimal modulation references can be directly obtained at each sampling period according to the duty cycles of two fixed voltage levels, and then be fed into the modulator to get gate signals. Hence, the developed method is very easy to be implemented with a very low calculation complexity, independent of the submodules (SMs) number. The switching state evaluation, cost function calculation and weighting factor selection are eliminated as well. In addition, this method has a satisfactory steady-state performance and equally distributed switching losses. The effectiveness the proposed method is verified by experiments. © 2021 IEEE.

Keyword:

Cost functions HVDC power transmission Model predictive control Modulation Petroleum reservoir evaluation Power converters Predictive control systems

Author Community:

  • [ 1 ] [Wang, Jinyu]Xi'An Jiaotong University, School of Electrical Engineering, Xi'an, China
  • [ 2 ] [Liu, Zhijie]Shandong University, School of Electrical Engineering, Jinan, China
  • [ 3 ] [Wang, Zhuodi]Shandong University, School of Electrical Engineering, Jinan, China
  • [ 4 ] [Huang, Jingjing]Xi'An Jiaotong University, School of Electronic and Information Engineering, Xi'an, China
  • [ 5 ] [Liu, Xiong]Jinan Univerisity, Energy Electricity Research Center, Zhuhai, China

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Year: 2021

Page: 98-103

Language: English

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 6

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