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A New Geometric Vector Optimization of Predictive Direct Power Control

Shuo Yan*, Jie Chen, Siew-Chong Tan, S. Y. Ron Hui

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

This article proposes a new vector optimization method suitable for predictive direct power control (P-DPC). Based on the geometric property of parallelograms and diamonds, a simple generic equation is established to form a set of evenly-distributed vectors in the converter voltage space through an iteration process. The optimum vector is selected from the vector set via the detection of the optimum sector and vector sequence number using a simple algebraic function rather than solving complex differential equations common in multivector P-DPC. The application time of the selected vector is optimized to further improve the control performance. It is demonstrated that the proposed method significantly reduces the computation burden, whilst achieving a remarkable steady-state and transient response, especially at the low sampling frequency. A set of simulation studies is conducted to compare the proposed method with its popular counterparts. In addition, experimental results are provided to verify the effectiveness of the new method. © 2019 IEEE.
Original languageEnglish
Pages (from-to)5427-5436
JournalIEEE Transactions on Power Electronics
Volume35
Issue number5
Online published29 Sept 2019
DOIs
Publication statusPublished - May 2020
Externally publishedYes

Funding

This work was supported in part by the Startup Fund of RMIT University under Grant RI-00101-021 and in part by the Hong Kong Research Council under Grant T23-701/14-N.

Research Keywords

  • Direct power control
  • model predictive control
  • PWM rectifiers

RGC Funding Information

  • RGC-funded

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