DOI QR코드

DOI QR Code

ZSCC suppression method for parallel three-level inverters based on model predictive control with virtual location vector

  • Ling Mao (School of Electric Power Engineering, Shanghai University of Electric Power) ;
  • Yuankai Li (School of Electric Power Engineering, Shanghai University of Electric Power) ;
  • Chao Pan (School of Electric Power Engineering, Shanghai University of Electric Power) ;
  • Jianlin Yang (State Power Investment Corporation Limited Wind Power Innovation Center) ;
  • Qin Hu (School of Electric Power Engineering, Shanghai University of Electric Power) ;
  • Yuncong Zheng (School of Electric Power Engineering, Shanghai University of Electric Power) ;
  • Jinbin Zhao (School of Electric Power Engineering, Shanghai University of Electric Power)
  • 투고 : 2023.05.25
  • 심사 : 2023.11.24
  • 발행 : 2024.04.20

초록

Parallel three-level neutral point clamped (3L-NPC) inverters are widely used in power conversion applications, such as new energy generation and high voltage inverters. However, the zero-sequence circulating current (ZSCC) between two inverters degrades the whole performance of the system. To suppress the ZSCC in parallel inverters and improve the quality of output current, this study proposes an MPC strategy based on the virtual location vector. First, to reduce the computational burden of MPC, the virtual location vector is constructed by the output current of two inverters so that the control of the parallel inverters is similar to that of a single inverter. Then, the virtual location vector is obtained by using the direct power control method. Finally, the sets of candidate voltage vectors for MPC are determined on the basis of this reference voltage vector and the magnitude of ZSCC. Moreover, the optimal vectors calculated by MPC are assigned to the two inverters. Compared with the traditional MPC strategy, the MPC strategy proposed in this study has better steady state and transient performance with less computational burden. The proposed method is validated in simulation and experimental platforms.

키워드

과제정보

This work was supported in part by the National Natural Science Foundation of China under Grant 52177184 and in part by the State Power Investment Corporation Limited Wind Power Innovation Center under Grant KYTC2021FD04.

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