A Multi-stage Model Predictive Control Method for Modular Multilevel Converter
Modular multilevel converter (MMC) has received extensive attention in the field of power transmission because of its advantages of strong scalability and high output power quality. A multi-stage model predictive control (MSMPC) method is proposed to solve the problems of complex weight factor de...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2024-04-01
|
| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2318 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Modular multilevel converter (MMC) has received extensive attention in the field of power transmission because of its advantages of strong scalability and high output power quality. A multi-stage model predictive control (MSMPC) method is proposed to solve the problems of complex weight factor design of traditional model predictive control and large harmonic component of bridge arm circulation. The proposed MSMPC method includes three stages: 1) In the first stage, the reference control option of output current tracking is obtained to realize AC current control; 2) In the second stage, two circulation factors are introduced to calculate the optimal number of sub modules (SMs) of the upper and lower bridge arms in the control of the previous stage; 3) In the third stage, a sub module predictive voltage grouping sorting method is proposed, which can effectively reduce the number of voltage sorting and switching frequency. Compared with the traditional MPC method, the proposed MSMPC method avoids the design of weighting factors, improves the performance of circulating current suppression, and reduces the computational load of the controller. Simulation and experimental results verify the effectiveness of the proposed MSMPC method. |
|---|---|
| ISSN: | 1007-2683 |