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Global Maximum Power Point Tracking under Shading Condition and Hotspot Detection Algorithms for Photovoltaic Systems

Author

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  • Jirada Gosumbonggot

    (Graduate School of Engineering and Science, Shibaura Institute of Technology, Tokyo 135-8548, Japan)

  • Goro Fujita

    (Department of Electrical Engineering, Shibaura Institute of Technology, Tokyo 135-8548, Japan)

Abstract

Photovoltaic (PV) technology has been gaining an increasing amount of attention as a renewable energy source. Irradiation and temperature are the two main factors which impact on PV system performance. When partial shading from the surroundings occurs, its incident shadow diminishes the irradiation and reduces the generated power. Moreover, shading affects the pattern of the power–voltage (P–V) characteristic curve to contain more than one power peak, causing difficulties when developing maximum power point tracking. Consequently, shading leads to a hotspot in which spreading the hotspot widely on the PV panel’s surface increases the heat and causes damage to the panel. Since it is not possible to access the circuit inside the PV cells, indirect measurement and fault detection methods are needed to perform them. This paper proposes the global maximum power point tracking method, including the shading detection and tracking algorithm, using the trend of slopes from each section of the curve. The effectiveness was confirmed from the dynamic short-term testing and real weather data. The hotspot-detecting algorithm is also proposed from the analysis of different PV arrays’ configuration, which is approved by the simulation’s result. Each algorithm is presented using the full mathematical equations and flowcharts. Results from the simulation show the accurate tracking result along with the fast-tracking response. The simulation also confirms the success of the proposed hotspot-detection algorithm, confirmed by the graphical and numerical results.

Suggested Citation

  • Jirada Gosumbonggot & Goro Fujita, 2019. "Global Maximum Power Point Tracking under Shading Condition and Hotspot Detection Algorithms for Photovoltaic Systems," Energies, MDPI, vol. 12(5), pages 1-23, March.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:5:p:882-:d:211740
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    References listed on IDEAS

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    1. Carlos Olalla & Md. Nazmul Hasan & Chris Deline & Dragan Maksimović, 2018. "Mitigation of Hot-Spots in Photovoltaic Systems Using Distributed Power Electronics," Energies, MDPI, vol. 11(4), pages 1-16, March.
    2. Jirada Gosumbonggot & Goro Fujita, 2019. "Partial Shading Detection and Global Maximum Power Point Tracking Algorithm for Photovoltaic with the Variation of Irradiation and Temperature," Energies, MDPI, vol. 12(2), pages 1-22, January.
    3. Pillai, Dhanup S. & Rajasekar, N., 2018. "A comprehensive review on protection challenges and fault diagnosis in PV systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 18-40.
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    Cited by:

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    2. Lan Li & Hao Wang & Xiangping Chen & Abid Ali Shah Bukhari & Wenping Cao & Lun Chai & Bing Li, 2019. "High Efficiency Solar Power Generation with Improved Discontinuous Pulse Width Modulation (DPWM) Overmodulation Algorithms," Energies, MDPI, vol. 12(9), pages 1-18, May.
    3. Marco Balato & Carlo Petrarca, 2020. "The Impact of Reconfiguration on the Energy Performance of the Distributed Maximum Power Point Tracking Approach in PV Plants," Energies, MDPI, vol. 13(6), pages 1-19, March.
    4. CH Hussaian Basha & C Rani, 2020. "Different Conventional and Soft Computing MPPT Techniques for Solar PV Systems with High Step-Up Boost Converters: A Comprehensive Analysis," Energies, MDPI, vol. 13(2), pages 1-27, January.
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