{"title":"Impact of Uncertainties of Fundamental Models on Simulated Silicon Solar Cell Efficiencies","authors":"S. Wasmer, A. Fell, J. Greulich","doi":"10.1109/PVSC.2018.8548137","DOIUrl":null,"url":null,"abstract":"We determine the uncertainties on simulated efficiencies of silicon solar cells due to uncertainties of the fundamental physical models. For this end, we refit well-known models of numerical device simulations in order to acquire the uncertainties of the model parameters from the underlying measurement data. In a metamodeling and Monte Carlo simulation study, we then deduce how these propagate to the simulated solar cell efficiency. This is done for 150 $\\mu$ m thick 1 $\\Omega$ cm p-type standard and advanced silicon passivated emitter and rear cells (PERC) and for the limiting efficiency of silicon solar cells. We find uncertainties given by one standard deviation of 0.021%abs for usual PERC solar cells and 0.068%abs in case of the limiting efficiency. In a variance based sensitivity analysis, we find the uncertainties of the model parameters of the Auger recombination and the minority charge carrier mobility to contribute the most to the efficiency uncertainty. Besides these, we determine comparably large efficiency discrepancies of up to 0.6%abs for the two most prominent bandgap narrowing models, highlighting the necessity of further research on this topic.","PeriodicalId":6558,"journal":{"name":"2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC)","volume":"3 1","pages":"2658-2662"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PVSC.2018.8548137","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We determine the uncertainties on simulated efficiencies of silicon solar cells due to uncertainties of the fundamental physical models. For this end, we refit well-known models of numerical device simulations in order to acquire the uncertainties of the model parameters from the underlying measurement data. In a metamodeling and Monte Carlo simulation study, we then deduce how these propagate to the simulated solar cell efficiency. This is done for 150 $\mu$ m thick 1 $\Omega$ cm p-type standard and advanced silicon passivated emitter and rear cells (PERC) and for the limiting efficiency of silicon solar cells. We find uncertainties given by one standard deviation of 0.021%abs for usual PERC solar cells and 0.068%abs in case of the limiting efficiency. In a variance based sensitivity analysis, we find the uncertainties of the model parameters of the Auger recombination and the minority charge carrier mobility to contribute the most to the efficiency uncertainty. Besides these, we determine comparably large efficiency discrepancies of up to 0.6%abs for the two most prominent bandgap narrowing models, highlighting the necessity of further research on this topic.
由于基本物理模型的不确定性,我们确定了硅太阳能电池模拟效率的不确定性。为此,我们对众所周知的数值器件模拟模型进行了改造,以便从潜在的测量数据中获得模型参数的不确定性。在元建模和蒙特卡罗模拟研究中,我们然后推断这些如何传播到模拟的太阳能电池效率。这是针对150 $\mu$ m厚1 $\Omega$ cm p型标准和先进的硅钝化发射极和后部电池(PERC)以及硅太阳能电池的极限效率进行的。我们发现一个标准差为0.021的不确定性%abs for usual PERC solar cells and 0.068%abs in case of the limiting efficiency. In a variance based sensitivity analysis, we find the uncertainties of the model parameters of the Auger recombination and the minority charge carrier mobility to contribute the most to the efficiency uncertainty. Besides these, we determine comparably large efficiency discrepancies of up to 0.6%abs for the two most prominent bandgap narrowing models, highlighting the necessity of further research on this topic.