RESEARCH ON PHOTOVOLTAIC MAXIMUM POWER POINT TRACKING BASED ON IMPROVED PSO-LGWO OPTIMIZATION

Wang Yulin; Sun Liying

doi:10.19912/j.0254-0096.tynxb.2023-1775

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (3) : 328-334. DOI: 10.19912/j.0254-0096.tynxb.2023-1775

RESEARCH ON PHOTOVOLTAIC MAXIMUM POWER POINT TRACKING BASED ON IMPROVED PSO-LGWO OPTIMIZATION

Wang Yulin, Sun Liying

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Abstract

When the photovoltaic array is subjected to uneven solar irradiation, its output characteristic curve will have multiple peak points. The conventional maximum power point tracking （MPPT） method may fall into the local peak point, resulting in that the photovoltaic array cannot operate at the maximum power point. In order to solve such problems, an algorithm based on improved particle swarm optimization combined with grey wolf algorithm and Levy flight module （PSO-LGWO） is proposed. In the function test and static shadow test, the algorithm can improve the convergence speed while ensuring the tracking accuracy of the algorithm compared with other grey wolf algorithms. In the dynamic shadow test, compared with the common MPPT method in the actual photovoltaic power station, it can jump out of the local optimal solution. When the solar irradiance changes greatly, it has faster convergence speed while ensuring the tracking accuracy of the algorithm.

Key words

maximum power point trackers / solar cells / solar power generation / grey wolf optimization（GWO） / particle swarm optimization（PSO）

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Wang Yulin, Sun Liying. RESEARCH ON PHOTOVOLTAIC MAXIMUM POWER POINT TRACKING BASED ON IMPROVED PSO-LGWO OPTIMIZATION[J]. Acta Energiae Solaris Sinica. 2025, 46(3): 328-334 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1775

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