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Parameter Optimization of Photovoltaic Solar Cell and Panel Using Genetic Algorithms Strategy

Parameter Optimization of Photovoltaic Solar Cell and Panel Using Genetic Algorithms Strategy
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Author(s): Benmessaoud Mohammed Tarik (University of Science and Technology of Oran, Algeria), Fatima Zohra Zerhouni (University of Science and Technology of Oran, Algeria), Amine Boudghene Stambouli (University of Science and Technology of Oran, Algeria), Mustapha Tioursi (University of Science and Technology of Oran, Algeria) and Aouad M'harer (University of Tissemsilt, Algeria)
Copyright: 2017
Pages: 20
Source title: Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-0788-8.ch052

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Abstract

In this chapter, we propose to perform a numerical technique based on genetic algorithms (GAs) to identify the electrical parameters (Is, Iph, Rs, Rsh, and n) of photovoltaic (PV) solar cells and modules. The one diode type approach is used to model the I–V characteristic of the solar cell. To extract electrical parameters, the approach is formulated as optimization problem. The GAs approach was used as a numerical technique in order to overcome problems involved in the local minima in the case optimization criteria. Compared to other methods, we find that the GAs is a very efficient technique to estimate the electrical parameters of photovoltaic solar cells and modules. Compared with other parameter extraction techniques, based on statistical study, results indicate the consistency and uniformity of method in terms of the quality of final solutions. In parallel, the simulated data with the extracted parameters of method base with GAs are in very good agreement with the experimental data in all cases.

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