免疫萤火虫算法在光伏阵列最大功率点跟踪中的应用

doi:10.19595/j.cnki.1000-6753.tces.190760

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Abstract The P-U curves exhibit complex multiple-peak characteristics if PV arrays operate under various partial shading conditions (PSC). In that case, if the maximum power point tracking can not be achieved quickly and accurately, it will lead to a large amount of energy loss. Therefore, it has become a hot topic to research a reliable maximum power tracking control algorithm to ensure that the PV system can still output maximum power under PSCs. In this paper, an immune firefly algorithm (IFA) is proposed, which utilizes vaccine data-base to shorten the convergence time of the algorithm and eliminates the influence of bad individuals in time by immune replenishment operation, in addition, IFA can reduce the steady-state oscillation by the improved motion equation. The simulations in static and dynamic environments verify that the immune firefly algorithm can track the global point under various partial shading conditions. Compared with conventional FA, IFA has faster convergence speed, and can effectively restrain the oscillation of voltage and power.

Key words： Potovoltaic (PV) firefly algorithm (FA) maximum power point tracking (MPPT) partial shading conditions (PSC)

Received: 25 June 2019 Published: 07 April 2020

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TM615

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	Zhang Mingrui
	Chen Zheyang
	Wei Li

Cite this article:

Zhang Mingrui,Chen Zheyang,Wei Li. Application of Immune Firefly Algorithms in Photovoltaic Array Maximum Power Point Tracking[J]. Transactions of China Electrotechnical Society, 2020, 35(7): 1553-1562.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.190760 OR https://dgjsxb.ces-transaction.com/EN/Y2020/V35/I7/1553

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