Design and characterization of effective solar cells
Publication Date
2022-05Journal Title
Energy Systems
ISSN
1868-3967
Publisher
Springer Science and Business Media LLC
Volume
13
Issue
2
Pages
355-382
Language
en
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Ojha, V., Jansen, G., Patanè, A., La Magna, A., Romano, V., & Nicosia, G. (2022). Design and characterization of effective solar cells. Energy Systems, 13 (2), 355-382. https://doi.org/10.1007/s12667-021-00451-x
Description
Funder: Università degli Studi di Catania
Abstract
<jats:title>Abstract</jats:title><jats:p>We propose a two-stage multi-objective optimization framework for full scheme solar cell <jats:italic>structure design and characterization</jats:italic>, <jats:italic>cost minimization</jats:italic> and <jats:italic>quantum efficiency maximization</jats:italic>. We evaluated structures of 15 different cell designs simulated by varying material types and photodiode doping strategies. At first, non-dominated sorting genetic algorithm II (NSGA-II) produced Pareto-optimal-solutions sets for respective cell designs. Then, on investigating quantum efficiencies of all cell designs produced by NSGA-II, we applied a new <jats:italic>multi-objective optimization algorithm II</jats:italic> (OptIA-II) to discover the Pareto fronts of select (three) best cell designs. Our designed OptIA-II algorithm improved the quantum efficiencies of all select cell designs and reduced their fabrication costs. We observed that the cell design comprising an optimally doped zinc-oxide-based transparent conductive oxide (TCO) layer and rough silver back reflector (BR) offered a quantum efficiency (<jats:inline-formula><jats:alternatives><jats:tex-math>$$Q_e$$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML">
<mml:msub>
<mml:mi>Q</mml:mi>
<mml:mi>e</mml:mi>
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</mml:math></jats:alternatives></jats:inline-formula>) of 0.6031. Overall, this paper provides a <jats:italic>full characterization</jats:italic> of cell structure designs. It derives relationship between quantum efficiency, <jats:inline-formula><jats:alternatives><jats:tex-math>$$Q_e$$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML">
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</mml:math></jats:alternatives></jats:inline-formula> of a cell with its TCO layer’s doping methods and TCO and BR layer’s material types. Our solar cells design characterization enables us to perform a cost-benefit analysis of solar cells usage in real-world applications.</jats:p>
Keywords
Original Paper, Thin-film silicon solar cell, Quantum efficiency, Maxwell simulation, Multi-objective optimization, Pareto optimality, Artificial immune systems, Optimization, Immunological algorithms, OptIA-II, Clonal selection algorithms
Identifiers
s12667-021-00451-x, 451
External DOI: https://doi.org/10.1007/s12667-021-00451-x
This record's URL: https://www.repository.cam.ac.uk/handle/1810/336133
Rights
Licence:
http://creativecommons.org/licenses/by/4.0/
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