Alternative approach to optimizing optical spacer layer thickness in solar cell using evolutionary algorithm
- Authors
- Vincent, Premkumar; Sergio, Gwenaelle Cunha; Jang, Jaewon; Kang, In Man; Lang, Philippe; Kim, Hyeok; Lee, Minho; Bae, Jin-Hyuk
- Issue Date
- Aug-2019
- Publisher
- IEEE
- Keywords
- organic solar cell; optical modelling; evolutionary algorithm; finite difference time domain
- Citation
- 2019 19TH INTERNATIONAL CONFERENCE ON NUMERICAL SIMULATION OF OPTOELECTRONIC DEVICES (NUSOD 2019), pp 87 - 88
- Pages
- 2
- Indexed
- SCOPUS
- Journal Title
- 2019 19TH INTERNATIONAL CONFERENCE ON NUMERICAL SIMULATION OF OPTOELECTRONIC DEVICES (NUSOD 2019)
- Start Page
- 87
- End Page
- 88
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/73084
- DOI
- 10.1109/nusod.2019.8806865
- ISSN
- 2158-3234
- Abstract
- This work is inspired by Darwin's biological evolution theory: natural selection. We propose to use genetic evolutionary algorithm to optimize the search for the optimal thickness in solar cells with regards to maximizing short-circuit current density. Optical spacer layer thickness need to be optimized in order to achieve maximum absorption of the incoming light by the solar cell. In order to obtain the best optical spacer thickness, we perform multiple simulations with different number of population, number of generations, mutation probability, number of bits, and selection and crossover methods. Our preliminary experiments show that the introduction of evolutionary algorithm result in a satisfactorily accurate search method when compared to brute-force. The future works on utilizing the full ability of evolutionary algorithm will be presented at the conference.
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