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

Qianjin Gui, Lei Wang, Chao Ding, Wenfa Xu, Xiaoyang Li, Feilong Yu and Haisen Wang ()
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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

Energies, 2025, vol. 18, issue 5, 1-14

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.

Keywords: photovoltaic power systems; partial shading; multi-peak power points; honey badger algorithm; maximum power point tracking (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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