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A Database Implementation for the Study of Crystalline Silicon PV Modules Behavior

机译：研究晶体硅光伏组件行为的数据库实现

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The work proposed here aims at providing scientists and decision-makers with a mean which will help in the performance modeling of PV modules. Based on one of the existing models of solar cells, we developed a behavioral database enriched by the information that can be gathered from the manufacturers' datasheets of the modules. By considering the extraction of the 5 parameters of the module as an optimization non-constraint problem at Standard Test Conditions (STC), analytical expressions without any simplification, derived from the main current-voltage equation are used. By choosing a wise initial guess value we evaluated those 5 unknows more accurately. Datasheets of 10 different types of solar modules that are installed in photovoltaic plants in Senegal were considered. Hence the methodology adopted and applied on them in the simulation process allowed us to replicate first their current-voltage and power-voltage characteristics in STC, then in changing environmental conditions. In the end, this work focused on the prediction of a twelfth part of the output power produced on the DC side before an Inverter Transformer Station (ITS) of one photovoltaic plant. The measurement values compared with the simulation results showed a good match for the same day over two years.
机译：本文提出的工作旨在为科学家和决策者提供一种手段，以帮助其对光伏组件的性能建模。基于现有的太阳能电池模型之一，我们开发了行为数据库，该数据库丰富了可以从模块制造商的数据表中收集的信息。通过考虑将模块的5个参数的提取作为标准测试条件（STC）的优化非约束问题，可以使用从主电流-电压方程式导出的没有任何简化的解析表达式。通过选择一个明智的初始猜测值，我们可以更准确地评估这5个未知数。考虑了安装在塞内加尔的光伏电站中的10种不同类型的太阳能模块的数据表。因此，在仿真过程中采用并应用于它们的方法使我们能够先在STC中复制它们的电流-电压和功率-电压特性，然后再在变化的环境条件下进行复制。最后，这项工作着重于预测一个光伏电站的逆变器站（ITS）之前在直流侧产生的输出功率的第十二部分。测量值与模拟结果相比，显示出两年中同一天的良好匹配。

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