4.7 Article

YieldOpt, a model to predict the power output and energy yield for concentrating photovoltaic modules

期刊

PROGRESS IN PHOTOVOLTAICS
卷 23, 期 3, 页码 385-397

出版社

WILEY
DOI: 10.1002/pip.2458

关键词

simulation; modeling; CPV modules; ambient conditions; SPICE; SMARTS2

资金

  1. Federal Ministry for the Environment, the Nature Conservation and Nuclear Safety (BMU) under the KoMGen project [0327567A]

向作者/读者索取更多资源

In this work, we discuss three empirical models and introduce one more detailed model named YieldOpt. All models can be used to calculate the power output and energy yield of concentrating photovoltaic (CPV) modules under different ambient conditions. The YieldOpt model combines various modeling approaches: simple model of the atmospheric radiative transfer of sunshine for the spectral irradiance, a finite element method for thermal expansion, ray tracing for the optics, and a SPICE network model for the triple-junction solar cell. YieldOpt uses a number of constant and variable input parameters, for example, the external quantum efficiency of the cells, the temperature-dependent spectral optical efficiencies of the optics, the tracking accuracy, the direct normal irradiance, the aerosol optical depth, and the temperature of the lens and the solar cell. To verify the accuracy of the models, the I-V characteristics of five CPV modules have been measured in a 10-min interval over a period of 1year in Freiburg, Germany. Four modules equipped with industrial-standard lattice-matched triple-junction solar cells and one module equipped with metamorphic triple-junction solar cells are investigated. The higher accuracy of YieldOpt compared with the three empirical models in predicting the power output of all five CPV modules during this period is demonstrated. The energy yield over a period of 1year was predicted for all five CPV modules with a maximum deviation of 5% by the three empirical models and 3% by YieldOpt. Copyright (c) 2014 John Wiley & Sons, Ltd.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据