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3-D Modeling of Multicrystalline Silicon Materials and Solar Cells

机译:多晶硅材料和太阳能电池的3-D建模

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摘要

We present a method to model large-area multicrystalline materials using Quokka3, based on artificially generated lifetime images created by combining injection-dependent intragrain lifetimes and defect recombination velocity maps extracted from photoluminescence-based lifetime images. It is found that simulations based only on measured lifetime images underestimate the detrimental impacts of crystal defects and, hence, overestimate the overall cell performance of multicrystalline silicon solar cells. As demonstration, we applied Quokka3 simulations to resolve various bulk recombination losses in industrial multicrystalline silicon solar cells, quantify the effects of phosphorus diffusion and hydrogenation on the final cell performance, and evaluate the detrimental impact of crystal defects on individual cell parameters. Through numerical simulations, this paper has also demonstrated the potential errors of using a single average value to predict the cell performance of inhomogeneous multicrystalline silicon materials. It is observed that the commonly used harmonic mean can provide a good indication for V-OC, but is less effective for predicting J(SC, )and is almost entirely ineffective for predicting the fill factor.
机译:我们提出了一种使用Quokka3建模大面积多晶材料的方法,该方法基于人工生成的寿命图像,该寿命图像是通过组合注入相关的晶粒内寿命和从基于光致发光的寿命图像中提取的缺陷重组速度图而创建的。发现仅基于测得的寿命图像的模拟低估了晶体缺陷的有害影响,因此高估了多晶硅太阳能电池的整体电池性能。作为演示,我们使用Quokka3模拟解决了工业多晶硅太阳能电池中的各种体重组损失,量化了磷扩散和氢化对最终电池性能的影响,并评估了晶体缺陷对单个电池参数的不利影响。通过数值模拟,本文还证明了使用单个平均值预测非均质多晶硅材料的电池性能的潜在误差。可以看出,常用的谐波均值可以很好地指示V-OC,但对J(SC,)的预测效果较差,对填充因子的预测几乎完全无效。

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