利用进化算法优化太阳能电池光学间隔层厚度的替代方法

Premkumar Vincent, Gwenaelle Cunha Sergio, Jaewon Jang, I. Kang, P. Lang, Hyeok Kim, Minho Lee, J. Bae
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引用次数: 2

摘要

这项工作的灵感来自达尔文的生物进化理论:自然选择。我们提出利用遗传进化算法来优化寻找太阳能电池中短路电流密度最大的最佳厚度。为了使太阳能电池最大限度地吸收入射光,需要对光学间隔层厚度进行优化。为了获得最佳的光学间隔厚度,我们使用不同的种群数、代数、突变概率、比特数以及选择和交叉方法进行了多次模拟。我们的初步实验表明,与暴力算法相比,引入进化算法可以获得令人满意的精确搜索方法。会议将介绍未来如何充分利用进化算法的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Alternative approach to optimizing optical spacer layer thickness in solar cell using evolutionary algorithm
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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