Model Predictive Control of Energy-Stored Quasi-Z-Source Inverter Without Weighting Factor

Tian Lan; Yan Zhang; Wanhong Zhang

doi:10.1109/ICIEA54703.2022.10006232

Model Predictive Control of Energy-Stored Quasi-Z-Source Inverter Without Weighting Factor

Tian Lan^*
, Yan Zhang
, Wanhong Zhang

^*Corresponding author for this work

Qinghai University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

When the quasi-Z-source inverter with energy storage (ES-qZSI) by model predictive control (MPC), an appropriate weighting factor is designed in the cost function to achieve the best possible performance from the system. However, adding weighting factors directly to a cost function produces both numerical instability and computational complexity, in addition to the inability to distinguish between the role of weighting factors and system dynamics in the performance of the relevant system. This paper proposes an improved MPC algorithm without weighting factors for the ES-qZSI system. The computational cost of MPC is significantly reduced by the voltage vector control method without affecting the control performance. Moreover, the inductance current term in the control logic is considered individually, thus eliminating its weighting factor. Compared with conventional MPC, computational efficiency and control performance are demonstrated via numerical simulation. The simulation results show a good dynamic and static performance for the improved algorithm.

Original language	English
Title of host publication	ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications
Editors	Wenxiang Xie, Shibin Gao, Xiaoqiong He, Xing Zhu, Jingjing Huang, Weirong Chen, Lei Ma, Haiyan Shu, Wenping Cao, Lijun Jiang, Zeliang Shu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	892-899
Number of pages	8
ISBN (Electronic)	9781665409841
DOIs	https://doi.org/10.1109/ICIEA54703.2022.10006232
Publication status	Published - 2022
Externally published	Yes
Event	17th IEEE Conference on Industrial Electronics and Applications, ICIEA 2022 - Chengdu, China Duration: 16 Dec 2022 → 19 Dec 2022

Publication series

Name	ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications

Conference

Conference	17th IEEE Conference on Industrial Electronics and Applications, ICIEA 2022
Country/Territory	China
City	Chengdu
Period	16/12/22 → 19/12/22

Keywords

MPC
energy storage
quasi-Z-source inverter (qZSI)
weighting factor

Access to Document

10.1109/ICIEA54703.2022.10006232

Cite this

Lan, T., Zhang, Y., & Zhang, W. (2022). Model Predictive Control of Energy-Stored Quasi-Z-Source Inverter Without Weighting Factor. In W. Xie, S. Gao, X. He, X. Zhu, J. Huang, W. Chen, L. Ma, H. Shu, W. Cao, L. Jiang, & Z. Shu (Eds.), ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications (pp. 892-899). (ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIEA54703.2022.10006232

Lan, Tian ; Zhang, Yan ; Zhang, Wanhong. / Model Predictive Control of Energy-Stored Quasi-Z-Source Inverter Without Weighting Factor. ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications. editor / Wenxiang Xie ; Shibin Gao ; Xiaoqiong He ; Xing Zhu ; Jingjing Huang ; Weirong Chen ; Lei Ma ; Haiyan Shu ; Wenping Cao ; Lijun Jiang ; Zeliang Shu. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 892-899 (ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications).

@inproceedings{4ef35a1578ce4e6888f665e7b73c8c73,

title = "Model Predictive Control of Energy-Stored Quasi-Z-Source Inverter Without Weighting Factor",

abstract = "When the quasi-Z-source inverter with energy storage (ES-qZSI) by model predictive control (MPC), an appropriate weighting factor is designed in the cost function to achieve the best possible performance from the system. However, adding weighting factors directly to a cost function produces both numerical instability and computational complexity, in addition to the inability to distinguish between the role of weighting factors and system dynamics in the performance of the relevant system. This paper proposes an improved MPC algorithm without weighting factors for the ES-qZSI system. The computational cost of MPC is significantly reduced by the voltage vector control method without affecting the control performance. Moreover, the inductance current term in the control logic is considered individually, thus eliminating its weighting factor. Compared with conventional MPC, computational efficiency and control performance are demonstrated via numerical simulation. The simulation results show a good dynamic and static performance for the improved algorithm.",

keywords = "MPC, energy storage, quasi-Z-source inverter (qZSI), weighting factor",

author = "Tian Lan and Yan Zhang and Wanhong Zhang",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 17th IEEE Conference on Industrial Electronics and Applications, ICIEA 2022 ; Conference date: 16-12-2022 Through 19-12-2022",

year = "2022",

doi = "10.1109/ICIEA54703.2022.10006232",

language = "English",

series = "ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "892--899",

editor = "Wenxiang Xie and Shibin Gao and Xiaoqiong He and Xing Zhu and Jingjing Huang and Weirong Chen and Lei Ma and Haiyan Shu and Wenping Cao and Lijun Jiang and Zeliang Shu",

booktitle = "ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications",

address = "United States",

}

Lan, T, Zhang, Y & Zhang, W 2022, Model Predictive Control of Energy-Stored Quasi-Z-Source Inverter Without Weighting Factor. in W Xie, S Gao, X He, X Zhu, J Huang, W Chen, L Ma, H Shu, W Cao, L Jiang & Z Shu (eds), ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications. ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications, Institute of Electrical and Electronics Engineers Inc., pp. 892-899, 17th IEEE Conference on Industrial Electronics and Applications, ICIEA 2022, Chengdu, China, 16/12/22. https://doi.org/10.1109/ICIEA54703.2022.10006232

Model Predictive Control of Energy-Stored Quasi-Z-Source Inverter Without Weighting Factor. / Lan, Tian; Zhang, Yan; Zhang, Wanhong.
ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications. ed. / Wenxiang Xie; Shibin Gao; Xiaoqiong He; Xing Zhu; Jingjing Huang; Weirong Chen; Lei Ma; Haiyan Shu; Wenping Cao; Lijun Jiang; Zeliang Shu. Institute of Electrical and Electronics Engineers Inc., 2022. p. 892-899 (ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Model Predictive Control of Energy-Stored Quasi-Z-Source Inverter Without Weighting Factor

AU - Lan, Tian

AU - Zhang, Yan

AU - Zhang, Wanhong

PY - 2022

Y1 - 2022

N2 - When the quasi-Z-source inverter with energy storage (ES-qZSI) by model predictive control (MPC), an appropriate weighting factor is designed in the cost function to achieve the best possible performance from the system. However, adding weighting factors directly to a cost function produces both numerical instability and computational complexity, in addition to the inability to distinguish between the role of weighting factors and system dynamics in the performance of the relevant system. This paper proposes an improved MPC algorithm without weighting factors for the ES-qZSI system. The computational cost of MPC is significantly reduced by the voltage vector control method without affecting the control performance. Moreover, the inductance current term in the control logic is considered individually, thus eliminating its weighting factor. Compared with conventional MPC, computational efficiency and control performance are demonstrated via numerical simulation. The simulation results show a good dynamic and static performance for the improved algorithm.

AB - When the quasi-Z-source inverter with energy storage (ES-qZSI) by model predictive control (MPC), an appropriate weighting factor is designed in the cost function to achieve the best possible performance from the system. However, adding weighting factors directly to a cost function produces both numerical instability and computational complexity, in addition to the inability to distinguish between the role of weighting factors and system dynamics in the performance of the relevant system. This paper proposes an improved MPC algorithm without weighting factors for the ES-qZSI system. The computational cost of MPC is significantly reduced by the voltage vector control method without affecting the control performance. Moreover, the inductance current term in the control logic is considered individually, thus eliminating its weighting factor. Compared with conventional MPC, computational efficiency and control performance are demonstrated via numerical simulation. The simulation results show a good dynamic and static performance for the improved algorithm.

KW - MPC

KW - energy storage

KW - quasi-Z-source inverter (qZSI)

KW - weighting factor

UR - https://www.scopus.com/pages/publications/85146899195

U2 - 10.1109/ICIEA54703.2022.10006232

DO - 10.1109/ICIEA54703.2022.10006232

M3 - Conference contribution

AN - SCOPUS:85146899195

T3 - ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications

SP - 892

EP - 899

BT - ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications

A2 - Xie, Wenxiang

A2 - Gao, Shibin

A2 - He, Xiaoqiong

A2 - Zhu, Xing

A2 - Huang, Jingjing

A2 - Chen, Weirong

A2 - Ma, Lei

A2 - Shu, Haiyan

A2 - Cao, Wenping

A2 - Jiang, Lijun

A2 - Shu, Zeliang

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 17th IEEE Conference on Industrial Electronics and Applications, ICIEA 2022

Y2 - 16 December 2022 through 19 December 2022

ER -

Lan T, Zhang Y, Zhang W. Model Predictive Control of Energy-Stored Quasi-Z-Source Inverter Without Weighting Factor. In Xie W, Gao S, He X, Zhu X, Huang J, Chen W, Ma L, Shu H, Cao W, Jiang L, Shu Z, editors, ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications. Institute of Electrical and Electronics Engineers Inc. 2022. p. 892-899. (ICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications). doi: 10.1109/ICIEA54703.2022.10006232

Model Predictive Control of Energy-Stored Quasi-Z-Source Inverter Without Weighting Factor

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