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The Design and Optimization of GaAs Single Solar Cells Using the Genetic Algorithm and Silvaco ATLAS
Joint Authors
Asselman, Adel
Attari, Kamal
Amhaimar, Lahcen
El yaakoubi, Ali
Bassou, Mounir
Source
International Journal of Photoenergy
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-11-12
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Single-junction solar cells are the most available in the market and the most simple in terms of the realization and fabrication comparing to the other solar devices.
However, these single-junction solar cells need more development and optimization for higher conversion efficiency.
In addition to the doping densities and compromises between different layers and their best thickness value, the choice of the materials is also an important factor on improving the efficiency.
In this paper, an efficient single-junction solar cell model of GaAs is presented and optimized.
In the first step, an initial model was simulated and then the results were processed by an algorithm code.
In this work, the proposed optimization method is a genetic search algorithm implemented in Matlab receiving ATLAS data to generate an optimum output power solar cell.
Other performance parameters such as photogeneration rates, external quantum efficiency (EQE), and internal quantum efficiency (EQI) are also obtained.
The simulation shows that the proposed method provides significant conversion efficiency improvement of 29.7% under AM1.5G illumination.
The other results were Jsc = 34.79 mA/cm2, Voc = 1 V, and fill factor (FF) = 85%.
American Psychological Association (APA)
Attari, Kamal& Amhaimar, Lahcen& El yaakoubi, Ali& Asselman, Adel& Bassou, Mounir. 2017. The Design and Optimization of GaAs Single Solar Cells Using the Genetic Algorithm and Silvaco ATLAS. International Journal of Photoenergy،Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1168471
Modern Language Association (MLA)
Attari, Kamal…[et al.]. The Design and Optimization of GaAs Single Solar Cells Using the Genetic Algorithm and Silvaco ATLAS. International Journal of Photoenergy No. 2017 (2017), pp.1-7.
https://search.emarefa.net/detail/BIM-1168471
American Medical Association (AMA)
Attari, Kamal& Amhaimar, Lahcen& El yaakoubi, Ali& Asselman, Adel& Bassou, Mounir. The Design and Optimization of GaAs Single Solar Cells Using the Genetic Algorithm and Silvaco ATLAS. International Journal of Photoenergy. 2017. Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1168471
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1168471