Journal of Electrical and Electronic Engineering

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Research on Maximum Power Point Algorithm Based on Adaptive Duty Cycle

Received: 27 December 2017    Accepted:     Published: 28 December 2017
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Abstract

In solar photovoltaic (PV) system it has been a tendency to extract the maximum output power from the PV panel with the decrease of production price. There are many novel control algorithms to track the maximum power point. The commonly used control algorithm is based on perturbation and observation algorithm (P&O). However, the traditional P&O method has some problems between the tracking speed and the control accuracy. In this paper, the mathematic model of photovoltaic cells is studied and a modified perturbation observation method is proposed. The algorithm adjusts the duty cycle step by step according to the variation of the slope of the power voltage curve. Simulink simulation of the PV module with the buck circuit proves the superiority of the variable duty cycle perturbation method in terms of tracking speed and stability compared with the traditional perturbation observation method.

DOI 10.11648/j.jeee.20170506.14
Published in Journal of Electrical and Electronic Engineering (Volume 5, Issue 6, December 2017)
Page(s) 235-241
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), 2024. Published by Science Publishing Group

Keywords

Photovoltaic System, Maximum Power Point, Variable Step Size, Adaptive

References
[1] Hengyang Luo, Huiqing Wen and Xingshuo Li. " Distributed MPPT control under partial shading condition, "2016 IEEE 8th International Power Electronics and Motion Control Conference (IPEMC-ECCE Asia), Hefei, 2016, pp. 928-932.
[2] K. L. Lian, J. H. Jhang and I. S. Tian, "A Maximum Power Point Tracking Method Based on Perturb-and-Observe Combined With Particle Swarm Optimization, "in IEEE Journal of Photovoltaics, vol. 4, no. 2, pp. 626-633, March 2014.
[3] N. Khaldi, H. Mahmoudi, M. Zazi and Y. Barradi, "The MPPT control of PV system by using neural networks based on Newton Raphson method," 2014 International Renewable and Sustainable Energy Conference (IRSEC), Ouarzazate, 2014, pp. 19-24.
[4] H. Renaudineau et al., "A PSO-Based Global MPPT Technique for Distributed PV Power Generation," in IEEE Transactions on Industrial Electronics, vol. 62, no. 2, pp. 1047-1058, Feb. 2015.
[5] X. Liu and L. A. C. Lopes, "An improved perturbation and observation maximum power point tracking algorithm for PV arrays, "2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551), 2004, pp. 2005-2010 Vol. 3.
[6] Y. Ma, T. Bai, X. Zhou and Z. Gao, "Summary of photo voltaic and maximum power point tracking," 2017 29th Chinese Control And Decision Conference (CCDC), Chongqing, 2017, pp. 2298-2303.
[7] K. Ding, X. Bian, H. Liu and T. Peng, "A MATLAB-Simulink-Based PV Module Model and Its Application Under Conditions of Nonuniform Irradiance, " in IEEE Transactions on Energy Conversion, vol. 27, no. 4, pp. 864-872, Dec. 2012.
[8] M. Azab, "A New Maximum Power Point Tracking for Photovoltaic Systems," WASET, vol. 34, 2008, pp. 571-574.
[9] R. Sankarganesh and S. Thangavel, "Maximum power point tracking in PV system using intelligence based P&O technique and hybrid cuk converter," 2012 International Conference on Emerging Trends in Science, Engineering and Technology (INCOSET), Tiruchirappalli, Tamilnadu, India, 2012, pp. 429-436.
[10] M. W. Rahman, C. Bathina, V. Karthikeyan and R. Prasanth, "Comparative analysis of developed incremental conductance (IC) and perturb & observe (P&O) MPPT algorithm for photovoltaic applications, "2016 10th International Conference on Intelligent Systems and Control (ISCO), Coimbatore, 2016, pp. 1-6.
Author Information
  • Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China

  • Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China

  • Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China

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  • APA Style

    Suting Liang, Lei Zhao, Wenjing Wang. (2017). Research on Maximum Power Point Algorithm Based on Adaptive Duty Cycle. Journal of Electrical and Electronic Engineering, 5(6), 235-241. https://doi.org/10.11648/j.jeee.20170506.14

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    ACS Style

    Suting Liang; Lei Zhao; Wenjing Wang. Research on Maximum Power Point Algorithm Based on Adaptive Duty Cycle. J. Electr. Electron. Eng. 2017, 5(6), 235-241. doi: 10.11648/j.jeee.20170506.14

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    AMA Style

    Suting Liang, Lei Zhao, Wenjing Wang. Research on Maximum Power Point Algorithm Based on Adaptive Duty Cycle. J Electr Electron Eng. 2017;5(6):235-241. doi: 10.11648/j.jeee.20170506.14

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  • @article{10.11648/j.jeee.20170506.14,
      author = {Suting Liang and Lei Zhao and Wenjing Wang},
      title = {Research on Maximum Power Point Algorithm Based on Adaptive Duty Cycle},
      journal = {Journal of Electrical and Electronic Engineering},
      volume = {5},
      number = {6},
      pages = {235-241},
      doi = {10.11648/j.jeee.20170506.14},
      url = {https://doi.org/10.11648/j.jeee.20170506.14},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.jeee.20170506.14},
      abstract = {In solar photovoltaic (PV) system it has been a tendency to extract the maximum output power from the PV panel with the decrease of production price. There are many novel control algorithms to track the maximum power point. The commonly used control algorithm is based on perturbation and observation algorithm (P&O). However, the traditional P&O method has some problems between the tracking speed and the control accuracy. In this paper, the mathematic model of photovoltaic cells is studied and a modified perturbation observation method is proposed. The algorithm adjusts the duty cycle step by step according to the variation of the slope of the power voltage curve. Simulink simulation of the PV module with the buck circuit proves the superiority of the variable duty cycle perturbation method in terms of tracking speed and stability compared with the traditional perturbation observation method.},
     year = {2017}
    }
    

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  • TY  - JOUR
    T1  - Research on Maximum Power Point Algorithm Based on Adaptive Duty Cycle
    AU  - Suting Liang
    AU  - Lei Zhao
    AU  - Wenjing Wang
    Y1  - 2017/12/28
    PY  - 2017
    N1  - https://doi.org/10.11648/j.jeee.20170506.14
    DO  - 10.11648/j.jeee.20170506.14
    T2  - Journal of Electrical and Electronic Engineering
    JF  - Journal of Electrical and Electronic Engineering
    JO  - Journal of Electrical and Electronic Engineering
    SP  - 235
    EP  - 241
    PB  - Science Publishing Group
    SN  - 2329-1605
    UR  - https://doi.org/10.11648/j.jeee.20170506.14
    AB  - In solar photovoltaic (PV) system it has been a tendency to extract the maximum output power from the PV panel with the decrease of production price. There are many novel control algorithms to track the maximum power point. The commonly used control algorithm is based on perturbation and observation algorithm (P&O). However, the traditional P&O method has some problems between the tracking speed and the control accuracy. In this paper, the mathematic model of photovoltaic cells is studied and a modified perturbation observation method is proposed. The algorithm adjusts the duty cycle step by step according to the variation of the slope of the power voltage curve. Simulink simulation of the PV module with the buck circuit proves the superiority of the variable duty cycle perturbation method in terms of tracking speed and stability compared with the traditional perturbation observation method.
    VL  - 5
    IS  - 6
    ER  - 

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