Journal of Power Electronics

The Korean Institute of Power Electronics (전력전자학회)
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Model predictive DC-component power control for grid-connected inverters under unbalanced network

  • Hu, Bihua (School of Automation and Electronic Information, Xiangtan University) ;
  • Chen, Zhiyong (School of Automation and Electronic Information, Xiangtan University) ;
  • Zhang, Zhi (Department of Electrical Engineering, Dongguan University of Technology) ;
  • Deng, Wenlang (School of Automation and Electronic Information, Xiangtan University) ;
  • Zhao, Dongdong (School of Automation and Electronic Information, Xiangtan University)
  • Received : 2020.03.11
  • Accepted : 2020.10.26
  • Published : 2021.01.20
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Abstract

Under an unbalanced network, model predictive control (MPPC) with a new definition of the instantaneous reactive power has attracted a great deal of attention due to its simple control structure and outstanding steady-state performance. However, the reactive power cannot precisely trace the nonzero reference. In this paper, a model predictive DC-component power control (MPDCPC) is proposed to tackle the above-mentioned problem. Additionally, the MPDCPC can eliminate oscillations on the reactive power and the negative-sequence current. Then, the corresponding mathematical formulas are derived to extract the DC-component powers, to calculate the DC-component power derivative and to modify the power reference. By regulating the DC-component power to trace the modified reference, the MPDCPC can reduce the current harmonic and remove the oscillations on the active power, reactive power or negative-sequence current. Simulation and experimental platforms are established to demonstrate the validity of MPDCPC. Results demonstrate that the MPDCPC can effectively suppress current distortion and remove oscillations on active power, reactive power or negative-sequence current. In addition, the MPDCPC can successfully break through the restrictions of the MPPC with a new definition of instantaneous reactive power.

Keywords

Acknowledgement

This work was supported in part by the National Natural Science Foundation of China under Grant 51807055, in part by Hunan Natural Science Foundation under Grant 2019JJ50052.

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