Solar panel refers either to a photovoltaics (PV) module, a solar hot water panel, or to a set of solar photovoltaics modules electrically connected and mounted on a supporting structure. A PV module is a packaged, connected assembly of solar cells. Solar panels can be used as a component of a larger photovoltaic system to generate and supply electricity in commercial and residential applications (Wikipedia, 2015 AU161: The in-text citation "Wikipedia, 2015" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. ).
Published in Chapter:
Parameter Optimization of Photovoltaic Solar Cell and Panel Using Genetic Algorithms Strategy
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: © 2016
|Pages: 20
DOI: 10.4018/978-1-4666-9644-0.ch022
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.