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Alternative approach to optimizing optical spacer layer thickness in solar cell using evolutionary algorithm

机译:使用进化算法优化太阳能电池中光学隔离层厚度的替代方法

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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.
机译:这项工作的灵感来自达尔文的生物进化理论:自然选择。我们建议使用遗传进化算法来优化搜索太阳能电池的最佳厚度,以最大程度地提高短路电流密度。为了使太阳能电池最大程度地吸收入射光,需要优化光学隔离层的厚度。为了获得最佳的光学垫片厚度,我们使用不同的种群数量,世代数量,突变概率,位数以及选择和交叉方法执行多次仿真。我们的初步实验表明,与蛮力相比,进化算法的引入导致令人满意的精确搜索方法。会议将介绍利用进化算法的全部功能的未来工作。

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