Model Predictive Control of Dual-Mode Energy-Stored Quasi-Z-Source Photovoltaic System

Yushan Liu; Xuyang Liu; Xiao Li; Haiwen Yuan; Yaosuo Xue

doi:10.1109/SGRE53517.2022.9774042

Model Predictive Control of Dual-Mode Energy-Stored Quasi-Z-Source Photovoltaic System

Yushan Liu, Xuyang Liu, Xiao Li, Haiwen Yuan, Yaosuo Xue

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

2 Scopus citations

Abstract

The energy-stored quasi-Z-source inverter (ES-qZSI) has attracted much attention for photovoltaic (PV) power generations, due to its capability to stabilize the PV power fluctuations and other advantages of Z-source inverter. Traditional ES-qZSI suffers from poor operation at night or cloudy days when PV power is extremely low. In order to overcome that, this paper proposes a model predictive control (MPC) strategy for an improved dual-mode ES-qZSI, which is designed to support all-weather operation of PV power generation system. The system predictive models in both day and night operating modes are derived. And the control strategy based on MPC is disclosed to ensure the high-performance operation of the system. Simulation is carried out on PV power fluctuation in daytime and switching between the two modes, to verify the effectiveness of proposed control strategy.

Original language	English
Title of host publication	3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665479080
DOIs	https://doi.org/10.1109/SGRE53517.2022.9774042
State	Published - 2022
Externally published	Yes
Event	3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 - Doha, Qatar Duration: Mar 20 2022 → Mar 22 2022

Publication series

Name	3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 - Proceedings

Conference

Conference	3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022
Country/Territory	Qatar
City	Doha
Period	03/20/22 → 03/22/22

Funding

ACKNOWLEDGMENT This work was supported in part by the National Natural Science Foundation of China under Grant 52107175, in part by the Beijing Nova Program under grant Z211100002121080, and in part by the Fundamental Research Funds for the Central Universities under Grant KG16076201, China.

Keywords

Energy storage
Model predictive control
Photovoltaic power systems
quasi-Z-source inverter

Access to Document

10.1109/SGRE53517.2022.9774042

Cite this

Liu, Y., Liu, X., Li, X., Yuan, H., & Xue, Y. (2022). Model Predictive Control of Dual-Mode Energy-Stored Quasi-Z-Source Photovoltaic System. In 3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 - Proceedings (3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SGRE53517.2022.9774042

Liu, Yushan ; Liu, Xuyang ; Li, Xiao et al. / Model Predictive Control of Dual-Mode Energy-Stored Quasi-Z-Source Photovoltaic System. 3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2022. (3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 - Proceedings).

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title = "Model Predictive Control of Dual-Mode Energy-Stored Quasi-Z-Source Photovoltaic System",

abstract = "The energy-stored quasi-Z-source inverter (ES-qZSI) has attracted much attention for photovoltaic (PV) power generations, due to its capability to stabilize the PV power fluctuations and other advantages of Z-source inverter. Traditional ES-qZSI suffers from poor operation at night or cloudy days when PV power is extremely low. In order to overcome that, this paper proposes a model predictive control (MPC) strategy for an improved dual-mode ES-qZSI, which is designed to support all-weather operation of PV power generation system. The system predictive models in both day and night operating modes are derived. And the control strategy based on MPC is disclosed to ensure the high-performance operation of the system. Simulation is carried out on PV power fluctuation in daytime and switching between the two modes, to verify the effectiveness of proposed control strategy.",

keywords = "Energy storage, Model predictive control, Photovoltaic power systems, quasi-Z-source inverter",

author = "Yushan Liu and Xuyang Liu and Xiao Li and Haiwen Yuan and Yaosuo Xue",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 ; Conference date: 20-03-2022 Through 22-03-2022",

year = "2022",

doi = "10.1109/SGRE53517.2022.9774042",

language = "English",

series = "3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 - Proceedings",

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

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Liu, Y, Liu, X, Li, X, Yuan, H & Xue, Y 2022, Model Predictive Control of Dual-Mode Energy-Stored Quasi-Z-Source Photovoltaic System. in 3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 - Proceedings. 3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022, Doha, Qatar, 03/20/22. https://doi.org/10.1109/SGRE53517.2022.9774042

Model Predictive Control of Dual-Mode Energy-Stored Quasi-Z-Source Photovoltaic System. / Liu, Yushan; Liu, Xuyang; Li, Xiao et al.
3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2022. (3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 - Proceedings).

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

TY - GEN

T1 - Model Predictive Control of Dual-Mode Energy-Stored Quasi-Z-Source Photovoltaic System

AU - Liu, Yushan

AU - Liu, Xuyang

AU - Li, Xiao

AU - Yuan, Haiwen

AU - Xue, Yaosuo

PY - 2022

Y1 - 2022

N2 - The energy-stored quasi-Z-source inverter (ES-qZSI) has attracted much attention for photovoltaic (PV) power generations, due to its capability to stabilize the PV power fluctuations and other advantages of Z-source inverter. Traditional ES-qZSI suffers from poor operation at night or cloudy days when PV power is extremely low. In order to overcome that, this paper proposes a model predictive control (MPC) strategy for an improved dual-mode ES-qZSI, which is designed to support all-weather operation of PV power generation system. The system predictive models in both day and night operating modes are derived. And the control strategy based on MPC is disclosed to ensure the high-performance operation of the system. Simulation is carried out on PV power fluctuation in daytime and switching between the two modes, to verify the effectiveness of proposed control strategy.

AB - The energy-stored quasi-Z-source inverter (ES-qZSI) has attracted much attention for photovoltaic (PV) power generations, due to its capability to stabilize the PV power fluctuations and other advantages of Z-source inverter. Traditional ES-qZSI suffers from poor operation at night or cloudy days when PV power is extremely low. In order to overcome that, this paper proposes a model predictive control (MPC) strategy for an improved dual-mode ES-qZSI, which is designed to support all-weather operation of PV power generation system. The system predictive models in both day and night operating modes are derived. And the control strategy based on MPC is disclosed to ensure the high-performance operation of the system. Simulation is carried out on PV power fluctuation in daytime and switching between the two modes, to verify the effectiveness of proposed control strategy.

KW - Energy storage

KW - Model predictive control

KW - Photovoltaic power systems

KW - quasi-Z-source inverter

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U2 - 10.1109/SGRE53517.2022.9774042

DO - 10.1109/SGRE53517.2022.9774042

M3 - Conference contribution

AN - SCOPUS:85130918341

T3 - 3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 - Proceedings

BT - 3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022

Y2 - 20 March 2022 through 22 March 2022

ER -

Liu Y, Liu X, Li X, Yuan H, Xue Y. Model Predictive Control of Dual-Mode Energy-Stored Quasi-Z-Source Photovoltaic System. In 3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2022. (3rd International Conference on Smart Grid and Renewable Energy, SGRE 2022 - Proceedings). doi: 10.1109/SGRE53517.2022.9774042

Model Predictive Control of Dual-Mode Energy-Stored Quasi-Z-Source Photovoltaic System

Abstract

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Keywords

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