Self-Optimized Drift-Avoidance MPPT Algorithm for Photovoltaic Systems

Xiaofeng Zhang; Jiaxing Song; Zhaotong Chen

doi:10.1109/ICCASIT55263.2022.9986947

Self-Optimized Drift-Avoidance MPPT Algorithm for Photovoltaic Systems

Xiaofeng Zhang
, Jiaxing Song
, Zhaotong Chen

Heilongjiang University of Science and Technology
University of Science and Technology Beijing

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

1 Citation (SciVal)

Abstract

Generally, photovoltaic (PV) power generation is easily affected by changes in environmental conditions, such as irradiance and temperature. To extract the power at maximum power point (MPP), the perturbation and observation (P&O) method is widely adopted in industrial maximum power point tracking (MPPT), considering the low implementing complexity. However, the drift issue easily occurs in conventional P&O MPPT under the rapidly increasing irradiance, which might reduce the conversion efficiency. To address this issue, a self-optimized drift-avoidance MPPT algorithm is proposed in this paper, introducing the PV current pointer and self-adaptive step size regulation ability. The effectiveness of the proposed MPPT algorithm is validated by various operating scenarios in MATLAB/Simulink. A fair comparison with other advanced MPPT controls is accrued to highlight the advances of the proposed control. The simulation comparison shows that the proposed algorithm has a faster tracking speed, higher steady-state accuracy, and more reliable drift suppression capability.

Original language	English
Title of host publication	Proceedings of 2022 IEEE 4th International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022
Editors	Huabo Sun
Publisher	IEEE
Pages	739-743
Number of pages	5
ISBN (Electronic)	9781665467667
DOIs	https://doi.org/10.1109/ICCASIT55263.2022.9986947
Publication status	Published - 27 Dec 2022
Externally published	Yes
Event	4th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022 - Dali, China Duration: 12 Oct 2022 → 14 Oct 2022

Publication series

Name	Proceedings of 2022 IEEE 4th International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022

Conference

Conference	4th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022
Country/Territory	China
City	Dali
Period	12/10/22 → 14/10/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Drift
MPPT Algorithms
P&O
Photovoltaic power
Self-Optimized

ASJC Scopus subject areas

Computer Science Applications
Information Systems
Information Systems and Management
Aerospace Engineering
Automotive Engineering
Safety, Risk, Reliability and Quality
Control and Optimization

Access to Document

10.1109/ICCASIT55263.2022.9986947

Cite this

Zhang, X., Song, J., & Chen, Z. (2022). Self-Optimized Drift-Avoidance MPPT Algorithm for Photovoltaic Systems. In H. Sun (Ed.), Proceedings of 2022 IEEE 4th International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022 (pp. 739-743). (Proceedings of 2022 IEEE 4th International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022). IEEE. https://doi.org/10.1109/ICCASIT55263.2022.9986947

Self-Optimized Drift-Avoidance MPPT Algorithm for Photovoltaic Systems. / Zhang, Xiaofeng; Song, Jiaxing; Chen, Zhaotong.
Proceedings of 2022 IEEE 4th International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022. ed. / Huabo Sun. IEEE, 2022. p. 739-743 (Proceedings of 2022 IEEE 4th International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022).

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

Zhang, X, Song, J & Chen, Z 2022, Self-Optimized Drift-Avoidance MPPT Algorithm for Photovoltaic Systems. in H Sun (ed.), Proceedings of 2022 IEEE 4th International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022. Proceedings of 2022 IEEE 4th International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022, IEEE, pp. 739-743, 4th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022, Dali, China, 12/10/22. https://doi.org/10.1109/ICCASIT55263.2022.9986947

Zhang X, Song J, Chen Z. Self-Optimized Drift-Avoidance MPPT Algorithm for Photovoltaic Systems. In Sun H, editor, Proceedings of 2022 IEEE 4th International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022. IEEE. 2022. p. 739-743. (Proceedings of 2022 IEEE 4th International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022). doi: 10.1109/ICCASIT55263.2022.9986947

Zhang, Xiaofeng ; Song, Jiaxing ; Chen, Zhaotong. / Self-Optimized Drift-Avoidance MPPT Algorithm for Photovoltaic Systems. Proceedings of 2022 IEEE 4th International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022. editor / Huabo Sun. IEEE, 2022. pp. 739-743 (Proceedings of 2022 IEEE 4th International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022).

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abstract = "Generally, photovoltaic (PV) power generation is easily affected by changes in environmental conditions, such as irradiance and temperature. To extract the power at maximum power point (MPP), the perturbation and observation (P\&O) method is widely adopted in industrial maximum power point tracking (MPPT), considering the low implementing complexity. However, the drift issue easily occurs in conventional P\&O MPPT under the rapidly increasing irradiance, which might reduce the conversion efficiency. To address this issue, a self-optimized drift-avoidance MPPT algorithm is proposed in this paper, introducing the PV current pointer and self-adaptive step size regulation ability. The effectiveness of the proposed MPPT algorithm is validated by various operating scenarios in MATLAB/Simulink. A fair comparison with other advanced MPPT controls is accrued to highlight the advances of the proposed control. The simulation comparison shows that the proposed algorithm has a faster tracking speed, higher steady-state accuracy, and more reliable drift suppression capability.",

keywords = "Drift, MPPT Algorithms, P\&O, Photovoltaic power, Self-Optimized",

author = "Xiaofeng Zhang and Jiaxing Song and Zhaotong Chen",

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AU - Zhang, Xiaofeng

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Y1 - 2022/12/27

N2 - Generally, photovoltaic (PV) power generation is easily affected by changes in environmental conditions, such as irradiance and temperature. To extract the power at maximum power point (MPP), the perturbation and observation (P&O) method is widely adopted in industrial maximum power point tracking (MPPT), considering the low implementing complexity. However, the drift issue easily occurs in conventional P&O MPPT under the rapidly increasing irradiance, which might reduce the conversion efficiency. To address this issue, a self-optimized drift-avoidance MPPT algorithm is proposed in this paper, introducing the PV current pointer and self-adaptive step size regulation ability. The effectiveness of the proposed MPPT algorithm is validated by various operating scenarios in MATLAB/Simulink. A fair comparison with other advanced MPPT controls is accrued to highlight the advances of the proposed control. The simulation comparison shows that the proposed algorithm has a faster tracking speed, higher steady-state accuracy, and more reliable drift suppression capability.

AB - Generally, photovoltaic (PV) power generation is easily affected by changes in environmental conditions, such as irradiance and temperature. To extract the power at maximum power point (MPP), the perturbation and observation (P&O) method is widely adopted in industrial maximum power point tracking (MPPT), considering the low implementing complexity. However, the drift issue easily occurs in conventional P&O MPPT under the rapidly increasing irradiance, which might reduce the conversion efficiency. To address this issue, a self-optimized drift-avoidance MPPT algorithm is proposed in this paper, introducing the PV current pointer and self-adaptive step size regulation ability. The effectiveness of the proposed MPPT algorithm is validated by various operating scenarios in MATLAB/Simulink. A fair comparison with other advanced MPPT controls is accrued to highlight the advances of the proposed control. The simulation comparison shows that the proposed algorithm has a faster tracking speed, higher steady-state accuracy, and more reliable drift suppression capability.

KW - Drift

KW - MPPT Algorithms

KW - P&O

KW - Photovoltaic power

KW - Self-Optimized

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ER -

Self-Optimized Drift-Avoidance MPPT Algorithm for Photovoltaic Systems

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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