RESEARCH ON PHOTOVOLTAIC MULTI-PEAK MAXIMUM POWER TRACKING CHARACTERISTICS BASED ON IMPROVED MAYFLY ALGORITHM

Zhao Zhiyong; Li Weijun; Zheng Miao; Zhu Yunqi; Zhang Yi

doi:10.19912/j.0254-0096.tynxb.2023-1069

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Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (12) : 77-84. DOI: 10.19912/j.0254-0096.tynxb.2023-1069

RESEARCH ON PHOTOVOLTAIC MULTI-PEAK MAXIMUM POWER TRACKING CHARACTERISTICS BASED ON IMPROVED MAYFLY ALGORITHM

Zhao Zhiyong, Li Weijun, Zheng Miao, Zhu Yunqi, Zhang Yi

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Abstract

An improved mayfly algorithm （EMA） is used to solve the problem of multiple peaks in solar ceu P-U graphs under partial shading conditions, where traditional maximum power point tracking （MPPT） algorithms tend to fall into local optimal solution, making it difficult to quickly and accurately find the global maximum power point of the PV system. Firstly, the male mayflies perform a global search to escape local optimal solution. Then, the female mayflies reduce system oscillations through random local search and mating. Finally, two different scenarios are set to verify the tracking accuracy and speed of the proposed algorithm. The results show that compared with particle swarm optimization （PSO） and grey wolf optimization （GWO）, the EMA reduces PV output power oscillations during the search process. Compared to PSO and GWO, EMA has significantly improved the tracking speed, allowing the solar cells to maintain high output power even under partial shading.

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PV generation / maximum power point tracking / improved Mayfly algorithm / partial shading / multi-peak / PV output characteristics

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Zhao Zhiyong, Li Weijun, Zheng Miao, Zhu Yunqi, Zhang Yi. RESEARCH ON PHOTOVOLTAIC MULTI-PEAK MAXIMUM POWER TRACKING CHARACTERISTICS BASED ON IMPROVED MAYFLY ALGORITHM[J]. Acta Energiae Solaris Sinica. 2024, 45(12): 77-84 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1069

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