MPPT Method Based on Improved Super-Twisting Algorithm

Mao Yi-dong

doi:doi:10.11648/j.sd.20221006.15

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MPPT Method Based on Improved Super-Twisting Algorithm

Mao Yi-dong

Published in Science Discovery (Volume 10, Issue 6)

Received: 21 October 2022 Accepted: 11 November 2022 Published: 14 November 2022

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Abstract

Maximum Power Point Tracking (MPPT) strategy is necessary to extract the maximum power production of a Photovoltaic system. Aiming at the obvious output chattering problem of traditional sliding mode control in the maximum power point tracking process of photovoltaic power generation, a sliding mode control maximum power point tracking strategy based on improved Super-Twisting algorithm is proposed. The Boost converter is used as the main circuit of the system. By analyzing the output characteristic curve of the photovoltaic cell, an improved Super-Twisting sliding mode controller is designed. The parameters of the improved Super-Twisting sliding mode controller are adjusted through the whale algorithm to optimize the controller parameters, greatly reducing the traditional sliding mode chattering and achieving maximum power point tracking. Finally, the stability of the improved Super-Twisting sliding mode control is analyzed by the Lyapunov function, and the simulation system is built in MATLAB/Simulink, under static and dynamic conditions, the simulations are compared with the traditional sliding mode control and perturb and observe method. The experimental results show that the sliding mode control strategy based on the improved Super-Twisting algorithm can effectively reduce the chattering problem of the traditional sliding mode controller, improve the convergence speed of the system, and has strong robustness when the external conditions change suddenly.

Published in	Science Discovery (Volume 10, Issue 6)
DOI	10.11648/j.sd.20221006.15
Page(s)	406-413
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

Photovoltaic Power Generation, Maximum Power Point Tracking, Super-Twisting, Whale Algorithm

References

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APA Style

Mao Yi-dong. (2022). MPPT Method Based on Improved Super-Twisting Algorithm. Science Discovery, 10(6), 406-413. https://doi.org/10.11648/j.sd.20221006.15

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ACS Style

Mao Yi-dong. MPPT Method Based on Improved Super-Twisting Algorithm. Sci. Discov. 2022, 10(6), 406-413. doi: 10.11648/j.sd.20221006.15

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AMA Style

Mao Yi-dong. MPPT Method Based on Improved Super-Twisting Algorithm. Sci Discov. 2022;10(6):406-413. doi: 10.11648/j.sd.20221006.15

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@article{10.11648/j.sd.20221006.15,
  author = {Mao Yi-dong},
  title = {MPPT Method Based on Improved Super-Twisting Algorithm},
  journal = {Science Discovery},
  volume = {10},
  number = {6},
  pages = {406-413},
  doi = {10.11648/j.sd.20221006.15},
  url = {https://doi.org/10.11648/j.sd.20221006.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20221006.15},
  abstract = {Maximum Power Point Tracking (MPPT) strategy is necessary to extract the maximum power production of a Photovoltaic system. Aiming at the obvious output chattering problem of traditional sliding mode control in the maximum power point tracking process of photovoltaic power generation, a sliding mode control maximum power point tracking strategy based on improved Super-Twisting algorithm is proposed. The Boost converter is used as the main circuit of the system. By analyzing the output characteristic curve of the photovoltaic cell, an improved Super-Twisting sliding mode controller is designed. The parameters of the improved Super-Twisting sliding mode controller are adjusted through the whale algorithm to optimize the controller parameters, greatly reducing the traditional sliding mode chattering and achieving maximum power point tracking. Finally, the stability of the improved Super-Twisting sliding mode control is analyzed by the Lyapunov function, and the simulation system is built in MATLAB/Simulink, under static and dynamic conditions, the simulations are compared with the traditional sliding mode control and perturb and observe method. The experimental results show that the sliding mode control strategy based on the improved Super-Twisting algorithm can effectively reduce the chattering problem of the traditional sliding mode controller, improve the convergence speed of the system, and has strong robustness when the external conditions change suddenly.},
 year = {2022}
}

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TY  - JOUR
T1  - MPPT Method Based on Improved Super-Twisting Algorithm
AU  - Mao Yi-dong
Y1  - 2022/11/14
PY  - 2022
N1  - https://doi.org/10.11648/j.sd.20221006.15
DO  - 10.11648/j.sd.20221006.15
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 406
EP  - 413
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20221006.15
AB  - Maximum Power Point Tracking (MPPT) strategy is necessary to extract the maximum power production of a Photovoltaic system. Aiming at the obvious output chattering problem of traditional sliding mode control in the maximum power point tracking process of photovoltaic power generation, a sliding mode control maximum power point tracking strategy based on improved Super-Twisting algorithm is proposed. The Boost converter is used as the main circuit of the system. By analyzing the output characteristic curve of the photovoltaic cell, an improved Super-Twisting sliding mode controller is designed. The parameters of the improved Super-Twisting sliding mode controller are adjusted through the whale algorithm to optimize the controller parameters, greatly reducing the traditional sliding mode chattering and achieving maximum power point tracking. Finally, the stability of the improved Super-Twisting sliding mode control is analyzed by the Lyapunov function, and the simulation system is built in MATLAB/Simulink, under static and dynamic conditions, the simulations are compared with the traditional sliding mode control and perturb and observe method. The experimental results show that the sliding mode control strategy based on the improved Super-Twisting algorithm can effectively reduce the chattering problem of the traditional sliding mode controller, improve the convergence speed of the system, and has strong robustness when the external conditions change suddenly.
VL  - 10
IS  - 6
ER  -

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Author Information

Mao Yi-dong

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

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Plain Text BibTeX RIS

APA Style

Mao Yi-dong. (2022). MPPT Method Based on Improved Super-Twisting Algorithm. Science Discovery, 10(6), 406-413. https://doi.org/10.11648/j.sd.20221006.15

Copy | Download

ACS Style

Mao Yi-dong. MPPT Method Based on Improved Super-Twisting Algorithm. Sci. Discov. 2022, 10(6), 406-413. doi: 10.11648/j.sd.20221006.15

Copy | Download

AMA Style

Mao Yi-dong. MPPT Method Based on Improved Super-Twisting Algorithm. Sci Discov. 2022;10(6):406-413. doi: 10.11648/j.sd.20221006.15

Copy | Download

@article{10.11648/j.sd.20221006.15,
  author = {Mao Yi-dong},
  title = {MPPT Method Based on Improved Super-Twisting Algorithm},
  journal = {Science Discovery},
  volume = {10},
  number = {6},
  pages = {406-413},
  doi = {10.11648/j.sd.20221006.15},
  url = {https://doi.org/10.11648/j.sd.20221006.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20221006.15},
  abstract = {Maximum Power Point Tracking (MPPT) strategy is necessary to extract the maximum power production of a Photovoltaic system. Aiming at the obvious output chattering problem of traditional sliding mode control in the maximum power point tracking process of photovoltaic power generation, a sliding mode control maximum power point tracking strategy based on improved Super-Twisting algorithm is proposed. The Boost converter is used as the main circuit of the system. By analyzing the output characteristic curve of the photovoltaic cell, an improved Super-Twisting sliding mode controller is designed. The parameters of the improved Super-Twisting sliding mode controller are adjusted through the whale algorithm to optimize the controller parameters, greatly reducing the traditional sliding mode chattering and achieving maximum power point tracking. Finally, the stability of the improved Super-Twisting sliding mode control is analyzed by the Lyapunov function, and the simulation system is built in MATLAB/Simulink, under static and dynamic conditions, the simulations are compared with the traditional sliding mode control and perturb and observe method. The experimental results show that the sliding mode control strategy based on the improved Super-Twisting algorithm can effectively reduce the chattering problem of the traditional sliding mode controller, improve the convergence speed of the system, and has strong robustness when the external conditions change suddenly.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - MPPT Method Based on Improved Super-Twisting Algorithm
AU  - Mao Yi-dong
Y1  - 2022/11/14
PY  - 2022
N1  - https://doi.org/10.11648/j.sd.20221006.15
DO  - 10.11648/j.sd.20221006.15
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 406
EP  - 413
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20221006.15
AB  - Maximum Power Point Tracking (MPPT) strategy is necessary to extract the maximum power production of a Photovoltaic system. Aiming at the obvious output chattering problem of traditional sliding mode control in the maximum power point tracking process of photovoltaic power generation, a sliding mode control maximum power point tracking strategy based on improved Super-Twisting algorithm is proposed. The Boost converter is used as the main circuit of the system. By analyzing the output characteristic curve of the photovoltaic cell, an improved Super-Twisting sliding mode controller is designed. The parameters of the improved Super-Twisting sliding mode controller are adjusted through the whale algorithm to optimize the controller parameters, greatly reducing the traditional sliding mode chattering and achieving maximum power point tracking. Finally, the stability of the improved Super-Twisting sliding mode control is analyzed by the Lyapunov function, and the simulation system is built in MATLAB/Simulink, under static and dynamic conditions, the simulations are compared with the traditional sliding mode control and perturb and observe method. The experimental results show that the sliding mode control strategy based on the improved Super-Twisting algorithm can effectively reduce the chattering problem of the traditional sliding mode controller, improve the convergence speed of the system, and has strong robustness when the external conditions change suddenly.
VL  - 10
IS  - 6
ER  -

Copy | Download