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Title: Multi-Vector Model Predictive Power Control of Three-Phase Rectifiers with Reduced Power Ripples Under Nonideal Grid Conditions
Authors: Zhou, Dehong
Tu, Pengfei
Tang, Yi
Keywords: Reactive Power
Voltage Control
Issue Date: 2018
Source: Zhou, D., Tu, P., & Tang, Y. (2018). Multi-Vector Model Predictive Power Control of Three-Phase Rectifiers with Reduced Power Ripples Under Nonideal Grid Conditions. IEEE Transactions on Industrial Electronics, in press.
Series/Report no.: IEEE Transactions on Industrial Electronics
Abstract: Model predictive power control (MPPC) is a promising control scheme for bidirectional AC/DC rectifiers. However, the control performance of conventional MPPC deteriorates under nonideal grid conditions. Furthermore, the one-switching-vector-per-control-interval characteristic of conventional MPPC leads to high ripples of control variables. To improve the steady-state performance of rectifiers under nonideal grid voltage conditions, a multi-vector model predictive power control (MV-MPPC) scheme is proposed. The proposed method presents a constant-switching-frequency and better steady-state control performance without increasing its sampling frequency. By selecting two active vectors and one zero vector, the range of optimal vector for active and reactive power regulation can be extended from fixed phase and magnitude to arbitrary phase and magnitude. Incorporated with a second-order generalized integrator (SOGI) for obtaining the quadrature component of grid voltage, the proposed method is applicable to the grid conditions where low-order harmonics exist. The preliminary calculation is adopted to avoid repetitive computation of the predicted values in the implementation of MV-MPPC, which reduces the calculation burden of the proposed scheme. A thorough experimental evaluation of the proposed scheme with the conventional MPPC (C-MPPC) and duty-optimal MPPC (DO-MPPC) has been conducted to validate the superiority of the proposed MV-MPPC solution.
ISSN: 0278-0046
DOI: 10.1109/TIE.2018.2798583
Rights: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [].
Fulltext Permission: open
Fulltext Availability: With Fulltext
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