Simplified Model Predictive Control of Low-Loss Grid-Connected Inverter

Liu Chunxi; Zhang Tianqi; Liu Zhile; Zhao Yucheng; Tian Baoqi

doi:doi:10.11648/j.sd.20221006.25

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Simplified Model Predictive Control of Low-Loss Grid-Connected Inverter

Liu Chunxi, Zhang Tianqi, Liu Zhile, Zhao Yucheng, Tian Baoqi

Published in Science Discovery (Volume 10, Issue 6)

Received: 21 October 2022 Accepted: 29 November 2022 Published: 8 December 2022

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Abstract

The finite control set model predictive control (FCS-MPC) for grid-connected inverter requires ergodic optimization and there are unnecessary switching actions, resulting in large system computation and switching loss. In order to solve the problem of large system computation, a simplified model predictive control method for grid-connected inverter was proposed. Based on deadbeat control principle, this control method judges the sector position after obtaining the virtual reference voltage vector. Only one prediction and one sector judgment are required to select the optimal switching vector, which reduces the system computation while ensuring the current control accuracy. In order to solve the problem of large switching loss of the system, an event-triggered control method based on zero vector optimization for grid-connected inverter was introduced. This control method reduces the switching action times of switching devices at the peak current by eliminating redundant optimization operations, thus reducing the switching loss. In addition, the event-triggered control is triggered only when the error exceeds the set threshold, which eliminates redundant optimization operations and reduces the system computation, thus further improving the dynamic response speed of the system. Finally, the proposed low-loss simplified model predictive control method (S-MPC) was compared with the FCS-MPC method and the cost function optimization-MPC method respectively. The simulation results show that the proposed control method is effective.

Published in	Science Discovery (Volume 10, Issue 6)
DOI	10.11648/j.sd.20221006.25
Page(s)	474-481
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Grid Connected Inverter, Power Loss, FCS-MPC, Deadbeat Control, Event-Triggered Control

References

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[3]	Kouro S, Cortes P, Vargas R, et al. Model predictive control-a simple and powerful method to control power converters [J]. IEEE Transactions on Industrial Electronics, 2009, 56 (6): 1826-1838.
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[5]	Preindl M, Bolognani S. Model predictive direct speed control with finite control set of PMSM drive systems [J]. IEEE Transactions on Power Electronics, 2013, 28 (2): 1007-1015.
[6]	XIA C L, LIU T, SHI T N, et al. A simplified finite control set model predictive control for power converters [J]. IEEE Transactions on Industrial Informatics, 2014, 10 (2): 991-1 002.
[7]	张永昌, 杨海涛, 魏香龙. 基于快速矢量选择的永磁同步电机模型预测控制 [J]. 电工技术学报, 2016, 31 (6): 66-73.
[8]	张学瑾. 并网逆变器的鲁棒定频模型预测控制研究(硕士学位论文) [D]. 合肥工业大学, 2020.
[9]	郭磊磊, 晋玉祥, 罗魁. 改进的低损耗并网逆变器双矢量模型预测电流控制方法 [J]. 电力自动化设备, 2019, 39 (10): 136-142.
[10]	金楠, 窦智峰, 李琰琰, 等. 电压源并网变换器有限控制集预测电流控制 [J]. 电机与控制学报, 2019, 23 (9): 123-130.
[11]	Kwak S, Park J C. Predictive control method with future zero-sequence voltage to reduce switching losses in three-phase voltage source inverters [J]. IEEE Transactions on Power Electronics, 2014, 30 (3): 1558-1566.
[12]	WANG B F, HUANG J J, WEN C Y, et al. Event-triggered model control predictive for power converters [J]. IEEE Transactions on Industrial Electronics, 2021, 68 (1): 715- 720.
[13]	窦智峰, 晋玉祥, 郭磊磊, 等. 损耗均衡分布的低耗逆变器模型预测控制研究 [J]. 可再生能源, 2018, 36 (9): 1355-1361.

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APA Style

Liu Chunxi, Zhang Tianqi, Liu Zhile, Zhao Yucheng, Tian Baoqi. (2022). Simplified Model Predictive Control of Low-Loss Grid-Connected Inverter. Science Discovery, 10(6), 474-481. https://doi.org/10.11648/j.sd.20221006.25

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ACS Style

Liu Chunxi; Zhang Tianqi; Liu Zhile; Zhao Yucheng; Tian Baoqi. Simplified Model Predictive Control of Low-Loss Grid-Connected Inverter. Sci. Discov. 2022, 10(6), 474-481. doi: 10.11648/j.sd.20221006.25

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AMA Style

Liu Chunxi, Zhang Tianqi, Liu Zhile, Zhao Yucheng, Tian Baoqi. Simplified Model Predictive Control of Low-Loss Grid-Connected Inverter. Sci Discov. 2022;10(6):474-481. doi: 10.11648/j.sd.20221006.25

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@article{10.11648/j.sd.20221006.25,
  author = {Liu Chunxi and Zhang Tianqi and Liu Zhile and Zhao Yucheng and Tian Baoqi},
  title = {Simplified Model Predictive Control of Low-Loss Grid-Connected Inverter},
  journal = {Science Discovery},
  volume = {10},
  number = {6},
  pages = {474-481},
  doi = {10.11648/j.sd.20221006.25},
  url = {https://doi.org/10.11648/j.sd.20221006.25},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20221006.25},
  abstract = {The finite control set model predictive control (FCS-MPC) for grid-connected inverter requires ergodic optimization and there are unnecessary switching actions, resulting in large system computation and switching loss. In order to solve the problem of large system computation, a simplified model predictive control method for grid-connected inverter was proposed. Based on deadbeat control principle, this control method judges the sector position after obtaining the virtual reference voltage vector. Only one prediction and one sector judgment are required to select the optimal switching vector, which reduces the system computation while ensuring the current control accuracy. In order to solve the problem of large switching loss of the system, an event-triggered control method based on zero vector optimization for grid-connected inverter was introduced. This control method reduces the switching action times of switching devices at the peak current by eliminating redundant optimization operations, thus reducing the switching loss. In addition, the event-triggered control is triggered only when the error exceeds the set threshold, which eliminates redundant optimization operations and reduces the system computation, thus further improving the dynamic response speed of the system. Finally, the proposed low-loss simplified model predictive control method (S-MPC) was compared with the FCS-MPC method and the cost function optimization-MPC method respectively. The simulation results show that the proposed control method is effective.},
 year = {2022}
}

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TY  - JOUR
T1  - Simplified Model Predictive Control of Low-Loss Grid-Connected Inverter
AU  - Liu Chunxi
AU  - Zhang Tianqi
AU  - Liu Zhile
AU  - Zhao Yucheng
AU  - Tian Baoqi
Y1  - 2022/12/08
PY  - 2022
N1  - https://doi.org/10.11648/j.sd.20221006.25
DO  - 10.11648/j.sd.20221006.25
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 474
EP  - 481
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20221006.25
AB  - The finite control set model predictive control (FCS-MPC) for grid-connected inverter requires ergodic optimization and there are unnecessary switching actions, resulting in large system computation and switching loss. In order to solve the problem of large system computation, a simplified model predictive control method for grid-connected inverter was proposed. Based on deadbeat control principle, this control method judges the sector position after obtaining the virtual reference voltage vector. Only one prediction and one sector judgment are required to select the optimal switching vector, which reduces the system computation while ensuring the current control accuracy. In order to solve the problem of large switching loss of the system, an event-triggered control method based on zero vector optimization for grid-connected inverter was introduced. This control method reduces the switching action times of switching devices at the peak current by eliminating redundant optimization operations, thus reducing the switching loss. In addition, the event-triggered control is triggered only when the error exceeds the set threshold, which eliminates redundant optimization operations and reduces the system computation, thus further improving the dynamic response speed of the system. Finally, the proposed low-loss simplified model predictive control method (S-MPC) was compared with the FCS-MPC method and the cost function optimization-MPC method respectively. The simulation results show that the proposed control method is effective.
VL  - 10
IS  - 6
ER  -

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Author Information

Liu Chunxi

Faculty of Electrical and Control Engineering, Liaoning Technical University, Huludao, China
Zhang Tianqi

Faculty of Electrical and Control Engineering, Liaoning Technical University, Huludao, China
Liu Zhile

Faculty of Electrical and Control Engineering, Liaoning Technical University, Huludao, China
Zhao Yucheng

Faculty of Electrical and Control Engineering, Liaoning Technical University, Huludao, China
Tian Baoqi

Faculty of Electrical and Control Engineering, Liaoning Technical University, Huludao, China

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Plain Text BibTeX RIS

APA Style

Liu Chunxi, Zhang Tianqi, Liu Zhile, Zhao Yucheng, Tian Baoqi. (2022). Simplified Model Predictive Control of Low-Loss Grid-Connected Inverter. Science Discovery, 10(6), 474-481. https://doi.org/10.11648/j.sd.20221006.25

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ACS Style

Liu Chunxi; Zhang Tianqi; Liu Zhile; Zhao Yucheng; Tian Baoqi. Simplified Model Predictive Control of Low-Loss Grid-Connected Inverter. Sci. Discov. 2022, 10(6), 474-481. doi: 10.11648/j.sd.20221006.25

Copy | Download

AMA Style

Liu Chunxi, Zhang Tianqi, Liu Zhile, Zhao Yucheng, Tian Baoqi. Simplified Model Predictive Control of Low-Loss Grid-Connected Inverter. Sci Discov. 2022;10(6):474-481. doi: 10.11648/j.sd.20221006.25

Copy | Download

@article{10.11648/j.sd.20221006.25,
  author = {Liu Chunxi and Zhang Tianqi and Liu Zhile and Zhao Yucheng and Tian Baoqi},
  title = {Simplified Model Predictive Control of Low-Loss Grid-Connected Inverter},
  journal = {Science Discovery},
  volume = {10},
  number = {6},
  pages = {474-481},
  doi = {10.11648/j.sd.20221006.25},
  url = {https://doi.org/10.11648/j.sd.20221006.25},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20221006.25},
  abstract = {The finite control set model predictive control (FCS-MPC) for grid-connected inverter requires ergodic optimization and there are unnecessary switching actions, resulting in large system computation and switching loss. In order to solve the problem of large system computation, a simplified model predictive control method for grid-connected inverter was proposed. Based on deadbeat control principle, this control method judges the sector position after obtaining the virtual reference voltage vector. Only one prediction and one sector judgment are required to select the optimal switching vector, which reduces the system computation while ensuring the current control accuracy. In order to solve the problem of large switching loss of the system, an event-triggered control method based on zero vector optimization for grid-connected inverter was introduced. This control method reduces the switching action times of switching devices at the peak current by eliminating redundant optimization operations, thus reducing the switching loss. In addition, the event-triggered control is triggered only when the error exceeds the set threshold, which eliminates redundant optimization operations and reduces the system computation, thus further improving the dynamic response speed of the system. Finally, the proposed low-loss simplified model predictive control method (S-MPC) was compared with the FCS-MPC method and the cost function optimization-MPC method respectively. The simulation results show that the proposed control method is effective.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - Simplified Model Predictive Control of Low-Loss Grid-Connected Inverter
AU  - Liu Chunxi
AU  - Zhang Tianqi
AU  - Liu Zhile
AU  - Zhao Yucheng
AU  - Tian Baoqi
Y1  - 2022/12/08
PY  - 2022
N1  - https://doi.org/10.11648/j.sd.20221006.25
DO  - 10.11648/j.sd.20221006.25
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 474
EP  - 481
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20221006.25
AB  - The finite control set model predictive control (FCS-MPC) for grid-connected inverter requires ergodic optimization and there are unnecessary switching actions, resulting in large system computation and switching loss. In order to solve the problem of large system computation, a simplified model predictive control method for grid-connected inverter was proposed. Based on deadbeat control principle, this control method judges the sector position after obtaining the virtual reference voltage vector. Only one prediction and one sector judgment are required to select the optimal switching vector, which reduces the system computation while ensuring the current control accuracy. In order to solve the problem of large switching loss of the system, an event-triggered control method based on zero vector optimization for grid-connected inverter was introduced. This control method reduces the switching action times of switching devices at the peak current by eliminating redundant optimization operations, thus reducing the switching loss. In addition, the event-triggered control is triggered only when the error exceeds the set threshold, which eliminates redundant optimization operations and reduces the system computation, thus further improving the dynamic response speed of the system. Finally, the proposed low-loss simplified model predictive control method (S-MPC) was compared with the FCS-MPC method and the cost function optimization-MPC method respectively. The simulation results show that the proposed control method is effective.
VL  - 10
IS  - 6
ER  -

Copy | Download