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A hybrid global maximum power point tracking method based on butterfly particle swarm optimization and perturb and observe algorithms for a photovoltaic system under partially shaded conditions
International Transactions on Electrical Energy Systems ( IF 2.3 ) Pub Date : 2020-07-28 , DOI: 10.1002/2050-7038.12543
Dileep Krishna Mathi 1 , Ramulu Chinthamalla 1
Affiliation  

In this paper, a new hybrid global maximum power point tracking (GMPPT) technique is proposed for faster and accurate tracking of global maximum power point (GMPP) without premature convergence. It is a combination of modified particle swarm optimization (PSO) and perturb and observe (P&O) methods. The proposed GMPPT technique, adaptive butterfly PSO (ABF‐PSO) uses butterfly swarm intelligence for modifying the conventional PSO algorithm with parameter tuning to avoid premature convergence.

中文翻译:

基于蝴蝶粒子群优化和扰动观测算法的部分阴影条件下的混合全局最大功率点跟踪方法

本文提出了一种新的混合全局最大功率点跟踪(GMPPT)技术,可以在不提前收敛的情况下更快,更准确地跟踪全局最大功率点(GMPP)。它是改进的粒子群优化(PSO)和摄动与观察(P&O)方法的结合。提出的GMPPT技术,自适应蝶形PSO(ABF-PSO)使用蝶形群智能,通过参数调整来修改常规PSO算法,以避免过早收敛。
更新日期:2020-07-28
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