PV multi-peak MPPT control based on improved parrot algorithm
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1.College of Electrical and New Energy, Three Gorges University,Yichang 443002, China; 2.Hubei Provincial Collaborative Innovation Center for New Energy Microgrid,Yichang 443002, China

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TN911.34

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    Abstract:

    Aiming at the problem that PV arrays show multipeak mutation under uneven light conditions, which leads to the imbalance of the traditional maximum power point tracking, an MPPT control based on the Improved Parrot Algorithm is proposed. Firstly, the Halton sequence is considered for population initialization to make the diversity change significant; secondly, the tangent flight mechanism in the Tangent Search Algorithm is selected to reduce the dynamic jumps and overcome the problems of precocity and local polarity; and later, the secondary update is performed by the parrot somersaulting foraging strategy to reduce the adaptive range and accelerate the convergence. Comparing the traditional parrot algorithm, the golden jackal algorithm and the gray wolf optimization algorithm, the test results show that the improved parrot algorithm′s MPPT control tracking efficiency is 98.23%, 97.26%, 96.91% and 96.81%, and the tracking time is 0.077 s, 0.112 s, 0.127 s, and 0.156 s, respectively, and the tracking accuracy and rate are significantly higher than the remaining three algorithms.

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  • Received:
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  • Online: November 04,2024
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