Journal of Power Electronics

The Korean Institute of Power Electronics (전력전자학회)
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Fix-frequency robust power model predictive control method for three-phase PWM rectifiers under unbalanced grid conditions

  • Guo, Xin (Department of Information and Control Engineering, Xi'an University of Technology) ;
  • Xiao, Min (Department of Information and Control Engineering, Xi'an University of Technology) ;
  • Gao, Yu-er (Department of Information and Control Engineering, Xi'an University of Technology) ;
  • Wang, Qingyu (Department of Information and Control Engineering, Xi'an University of Technology) ;
  • Wan, Yihao (Department of Information and Control Engineering, Xi'an University of Technology)
  • Received : 2019.11.10
  • Accepted : 2020.06.20
  • Published : 2020.09.20
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Abstract

Under unbalanced grid conditions, the controller design of a three-phase pulse width modulation (PWM) rectifier is based on an instantaneous power model. By calculating the current references of the converter according to the instantaneous power model, traditional voltage-oriented control (VOC) methods realize the positive-sequence and negative-sequence active and reactive current control of the converter separately using the proportional-integral (PI) controller. However, due to the inner current loop control structure of the traditional VOC method, it is impossible to realize the regulation of all six power components in a common instantaneous power model under an unbalanced grid. Meanwhile, the control performance of the traditional VOC method with a PI controller is degraded under the circuit parameters uncertainty condition. In this paper, a fixed switching frequency robust power model predictive control method (FRP-MPC) is proposed for three-phase PWM rectifiers under the unbalanced grid condition. The proposed control strategy has a number of advantages. An improved instantaneous power model is used for the fixed switching frequency model predictive controller design under the unbalanced grid condition, which has less power variables than the common instantaneous power model. The robustness of the MPC controller is improved by adding a robust item into the predictive model under circuit parameters uncertainty. Simulation and experiment results verify the effectiveness of the proposed control method.

Keywords

Acknowledgement

This work was supported in part by National Science Foundation of China (61803300), Shaanxi Province Research Program of Natural Science (2019JQ-017), Education Special Research Projects of Shaanxi Province (18JK0567) and Chinese Innovation and Entrepreneurship Training Program for College Students.

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