Research on MPPT Method under Uneven Illumination Intensity Based on BDMOA Algorithm

In photovoltaic power generation systems, uneven light due to external shading reduces efficiency. In the case of uneven illumination, the traditional MPPT algorithm has problems such as slow convergence speed, low accuracy, and large oscillation. In this paper, an improved MPPT algorithm based on d...

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Bibliographic Details
Published in2024 5th International Conference on Smart Grid and Energy Engineering (SGEE) pp. 434 - 437
Main Authors Ke, Dongxu, Kang, Bing, Ding, Guili, Wu, Hongtao, Cheng, Weiguo, He, Wenhua
Format Conference Proceeding
LanguageEnglish
Published IEEE 22.11.2024
Subjects
Accuracy
Convergence
Dwarf Mongoose Algorithm
Lighting
Maximum power point trackers
MPPT
Oscillators
Photovoltaic systems
Reverse Learning Strategy
Simulation
Sine-Cosine Strategies
Smart grids
Stability analysis
Thermal stability
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DOI10.1109/SGEE64306.2024.10865950

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Summary:In photovoltaic power generation systems, uneven light due to external shading reduces efficiency. In the case of uneven illumination, the traditional MPPT algorithm has problems such as slow convergence speed, low accuracy, and large oscillation. In this paper, an improved MPPT algorithm based on dwarf mongoose is proposed. In the initialization process, an improved reverse learning strategy is introduced to expand the population search range, so as to find the global optimal solution. The sine cosine strategy is introduced to accelerate the convergence speed of the algorithm and improve the convergence accuracy, so as to obtain a better solution. The simulation results show that the convergence speed of the algorithm is 0.33 seconds faster, and the oscillation is reduced.
DOI:10.1109/SGEE64306.2024.10865950