A Novel and General Stochastic Model of Photovoltaic Devices

1033615 RockettIntelligence优点拟议的研究将开发用于模拟太阳能光伏(PV)设备的高级数值建模程序，该程序依赖于一种新的随机方法来准确描述真实设备环境。该模型还将使对新型光伏结构的器件性能进行现实预测成为可能。这一功能将使太阳能光伏研究团体能够更好地评估新器件概念的优点。拟议的建模活动旨在从根本上改进目前模拟太阳能光伏器件的方式。现有的模型同时显式地求解描述载流子产生、传输和复合的方程。然而，所提出的模型将是随机的，使用随机过程来填充和清空状态，类似于真实的设备环境。随机方法应能显著提高模拟结果的稳定性和可靠性，并能适应比现有建模方法更复杂的物理和几何问题。建模程序还将包括自动数据拟合例程，以从常见的、用户提供的性能数据(例如，电压-光电流特性)中提取器件特性(例如，缺陷级别的估计)。宽频影响完整的软件包将在开放源码环境中可用，可通过网络访问，并包括一个模型输入参数的公共数据库，如材料属性。它的设计将使临时行业用户可以访问复杂而健壮的模型，以便从用户提供的数据中模拟或分析太阳能光伏设备的性能。将开发该软件包的教育版本，供本科生和研究生课程使用。所有这些活动将由一个由两名研究生和两名本科生组成的团队进行，他们将在开发创新软件工具方面获得专业知识，这些工具将支持太阳能光伏研究社区、行业并促进学生的学习。

1033615RockettIntellectual MeritThe proposed research will develop an advanced numerical modeling program for simulation of solar photovoltaic (PV) devices that relies on a new stochastic approach to accurately depict the real device environment. The model will also enable the realistic prediction of device performance for novel PV structures. This functionality will allow the solar PV research community to better assess the merits of new device concepts.The proposed modeling activities are designed to make fundamental improvements in the way solar PV devices are currently simulated. Existing models explicitly and simultaneously solve the equations that describe carrier generation, transport, and recombination. However, the proposed model will be stochastic, using random processes to fill and empty states, similar to the true device environment. The stochastic approach should provide a significant improvement in stability and reliability of the simulation results, and is adaptable to more complex physics and geometries than existing modeling approaches. The modeling program will also include an automated data fitting routine to extract device characteristics (e.g. estimation of defect levels) from common, user-supplied performance data (e.g. voltage-photocurrent characteristics).Broader ImpactsThe completed software package will be made available in an open source environment, be web accessible, and include a public database of model input parameters such as material properties. It will be designed so that casual industry users can access a sophisticated and robust model for simulation or analysis of solar PV device performance from user-supplied data. An educational version of the software package will be developed for use in undergraduate and graduate courses. All of these activities will be carried out by a team of two graduate and two undergraduate students, who will gain expertise in the development of innovative software tools that will support the solar PV research community, industry, and promote student learning.