Mismatch losses minimization in photovoltaic arrays by arranging modules applying a genetic algorithm

•Problem of mismatch power losses in photovoltaic arrays is explained.•Module sorting techniques are explained as conventional mismatch mitigation techniques.•A new solution is proposed, which stands for arranging modules applying a genetic algorithm.•Proposed solution gives lower mismatch losses an...

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Bibliographic Details
Published in:Solar energy 2014-10, Vol.108, p.467-478
Main Authors: Shirzadi, Samad, Hizam, H., Wahab, Noor Izzri Abdul
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Arrays
Direct energy conversion and energy accumulation
Electrical engineering. Electrical power engineering
Electrical power engineering
Energy
Equipments, installations and applications
Exact sciences and technology
Genetic algorithm
Genetics
Mismatch losses
Module sorting techniques
Natural energy
Photoelectric conversion
Photovoltaic
Photovoltaic cells
Photovoltaic conversion
Solar cells. Photoelectrochemical cells
Solar energy
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Summary:•Problem of mismatch power losses in photovoltaic arrays is explained.•Module sorting techniques are explained as conventional mismatch mitigation techniques.•A new solution is proposed, which stands for arranging modules applying a genetic algorithm.•Proposed solution gives lower mismatch losses and higher energy yield than sorting techniques do. Photovoltaic (PV) arrays consist of series and parallel connections of PV modules. Difference in current–voltage (I–V) characteristics among a batch of modules form an array causes power losses in PV systems referred to as mismatch losses. These power losses are conventionally reduced by module sorting techniques which sort modules based on an I–V parameter such as short circuit current, current at maximum power or maximum power. This work introduces a new method that employs genetic algorithm (GA) to find an arrangement of modules in an array which minimizes mismatch losses more effectively than conventional methods do. Extensive simulations are applied to adapt a GA to the problem of mismatch losses, find the arrangement and demonstrate its superiority over module sorting techniques in terms of mismatch losses decrement and energy yield increment. Instructions for practical application of the suggested method are also provided.
ISSN:0038-092X
1471-1257
DOI:10.1016/j.solener.2014.08.005