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

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 reliab...

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Bibliographic Details
Published in:Energies (Basel) 2019-08, Vol.12 (16), p.3083
Main Authors: Zhang, Mingrui, Chen, Zheyang, Li, Wei
Format: Article
Language:English
Subjects:
Algorithms
Computer simulation
Control theory
Convergence
Energy
Energy loss
Firefly algorithm (FA)
Immunological tolerance
Irradiance
Maximum power
maximum power point tracking (MPPT)
Methods
Optimization
partial shading conditions (PSC)
photovoltaic (PV)
Photovoltaic cells
Photovoltaics
Replenishment
Shading
Software
Support vector machines
Vaccines
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Summary: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.
ISSN:1996-1073
1996-1073
DOI:10.3390/en12163083