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An on-line MPPT algorithm for rapidly changing illuminations of solar arrays

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  • Hua, C.
  • Lin, J.

Abstract

Maximum power point tracking (MPPT) is usually used for a solar power system. Many maximum power tracking techniques have been considered in the past. The microprocessors with appropriate MPPT algorithms are favored because of their flexibility and compatibility with different solar arrays. Although the efficiency of MPPT algorithms is usually high, it drops noticeably in case of rapidly changing illumination conditions. The authors have proposed an improved MPPT algorithm based on the fact that the maximum power point (MPP) of solar arrays can be tracked accurately. The principle of energy conservation is used to develop the large- and small-signal model and transfer function for the solar power system. The work was carried out by both simulation and experiment on a current converter, by the digital signal processor (DSP) control, in MPPT mode under different illuminations. The results show that the proposed MPPT algorithm has successfully tracked the MPP in rapidly changing illumination conditions.

Suggested Citation

  • Hua, C. & Lin, J., 2003. "An on-line MPPT algorithm for rapidly changing illuminations of solar arrays," Renewable Energy, Elsevier, vol. 28(7), pages 1129-1142.
    • Handle: RePEc:eee:renene:v:28:y:2003:i:7:p:1129-1142
    DOI: 10.1016/S0960-1481(02)00214-8
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    Citations

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    Cited by:

    1. Joshi, Puneet & Arora, Sudha, 2017. "Maximum power point tracking methodologies for solar PV systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1154-1177.
    2. Issaadi, Wassila & Khireddine, Abdelkrim & Issaadi, Salim, 2016. "Management of a base station of a mobile network using a photovoltaic system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1570-1590.
    3. Altas, I.H. & Sharaf, A.M., 2008. "A novel maximum power fuzzy logic controller for photovoltaic solar energy systems," Renewable Energy, Elsevier, vol. 33(3), pages 388-399.
    4. Bendib, Boualem & Belmili, Hocine & Krim, Fateh, 2015. "A survey of the most used MPPT methods: Conventional and advanced algorithms applied for photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 637-648.
    5. Li, Shaowu & Attou, Amine & Yang, Yongchao & Geng, Dongshan, 2015. "A maximum power point tracking control strategy with variable weather parameters for photovoltaic systems with DC bus," Renewable Energy, Elsevier, vol. 74(C), pages 478-488.
    6. Gao, Xian-Zhong & Hou, Zhong-Xi & Guo, Zheng & Chen, Xiao-Qian, 2015. "Reviews of methods to extract and store energy for solar-powered aircraft," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 96-108.
    7. Seyedmahmoudian, M. & Horan, B. & Soon, T. Kok & Rahmani, R. & Than Oo, A. Muang & Mekhilef, S. & Stojcevski, A., 2016. "State of the art artificial intelligence-based MPPT techniques for mitigating partial shading effects on PV systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 435-455.
    8. Reza Reisi, Ali & Hassan Moradi, Mohammad & Jamasb, Shahriar, 2013. "Classification and comparison of maximum power point tracking techniques for photovoltaic system: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 433-443.
    9. Başoğlu, Mustafa Engin & Çakır, Bekir, 2016. "Comparisons of MPPT performances of isolated and non-isolated DC–DC converters by using a new approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1100-1113.

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