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Multi-Peak Photovoltaic Maximum Power Point Tracking Method Based on Honey Badger Algorithm Under Localized Shading Conditions

Author

Listed:
  • Qianjin Gui

    (State Grid Anqing Electric Power Supply Company, Anqing 246000, China)

  • Lei Wang

    (State Grid Anhui Electric Power Co., Ltd., Hefei 230000, China)

  • Chao Ding

    (State Grid Anhui Electric Power Co., Ltd., Hefei 230000, China)

  • Wenfa Xu

    (State Grid Anqing Electric Power Supply Company, Anqing 246000, China)

  • Xiaoyang Li

    (State Grid Anqing Electric Power Supply Company, Anqing 246000, China)

  • Feilong Yu

    (School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China)

  • Haisen Wang

    (School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China)

Abstract

The P-V and I-V curves of photovoltaic (PV) strings show multiple peaks when exposed to partial shading conditions (PSCs). The traditional maximum power point tracking (MPPT) method cannot track the global maximum power point (GMPP) due to the multi-peak characteristics, power fluctuation, and tracking speed. In this paper, a multi-peak PV MPPT method based on the honey badger algorithm (HBA) is proposed to track the GMPP in a localized shading environment. The performance of this method is also compared and analyzed with the traditional MPPT methods based on the perturbation observation (P&O) method and Particle Swarm Optimization (PSO) algorithm. The experimental results have proven that, compared with the MPPT methods based on P&O and PSO, the proposed multi-peak MPPT method based on the HBA algorithm has a faster tracking speed, higher tracking accuracy, and fewer iterations.

Suggested Citation

  • Qianjin Gui & Lei Wang & Chao Ding & Wenfa Xu & Xiaoyang Li & Feilong Yu & Haisen Wang, 2025. "Multi-Peak Photovoltaic Maximum Power Point Tracking Method Based on Honey Badger Algorithm Under Localized Shading Conditions," Energies, MDPI, vol. 18(5), pages 1-14, March.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:5:p:1258-:d:1605235
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    References listed on IDEAS

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    1. Li, Qiyu & Zhao, Shengdun & Wang, Mengqi & Zou, Zhongyue & Wang, Bin & Chen, Qixu, 2017. "An improved perturbation and observation maximum power point tracking algorithm based on a PV module four-parameter model for higher efficiency," Applied Energy, Elsevier, vol. 195(C), pages 523-537.
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