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An Immune Firefly Algorithm for Tracking the Maximum Power Point of PV Array under Partial Shading Conditions

Department of Electrical Engineering, Tongji University, Shanghai 201804, China
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Energies 2019, 12(16), 3083; https://doi.org/10.3390/en12163083
Received: 17 July 2019 / Revised: 4 August 2019 / Accepted: 5 August 2019 / Published: 9 August 2019
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Abstract

Photovoltaic (PV) string exhibits complex multiple-peak characteristics under various partial shading conditions (PSC). If the maximum power point tracking cannot be achieved quickly and accurately, it will lead to a large amount of energy loss. Therefore, it has become a hot topic to study a reliable maximum power tracking control algorithm to ensure the PV system can still output maximum power under PSC. This paper proposes an immune firefly algorithm (IFA), which utilizes vaccine data-base to shorten the convergence time, eliminates the influence of bad individuals in time by immune replenishment operation, and reduces the steady-state oscillation by the improving iteration formula. The simulations in static and dynamic environments verify that the immune firefly algorithm can track the maximum power point under various partial shading conditions. Compared with conventional firefly algorithm (FA), IFA has faster convergence speed, and can effectively restrain the oscillation of voltage and power. View Full-Text
Keywords: photovoltaic (PV); Firefly algorithm (FA); maximum power point tracking (MPPT); partial shading conditions (PSC) photovoltaic (PV); Firefly algorithm (FA); maximum power point tracking (MPPT); partial shading conditions (PSC)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Zhang, M.; Chen, Z.; Wei, L. An Immune Firefly Algorithm for Tracking the Maximum Power Point of PV Array under Partial Shading Conditions. Energies 2019, 12, 3083.

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