An adaptive method for the identification of the main features of photovoltaic modules

P. L. Carotenuto, G. Petrone, G. Spagnuolo
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Abstract

The recognition of the main features shown by a photovoltaic module through its current vs. voltage curve is of main interest in many applications, e.g. diagnosis and dynamical reconfiguration. Indeed, the automatic detection of the fact that it works in mismatched conditions, or some data directly related to its health conditions would be very useful. The curve is usually acquired by a switching converter, performing a voltage/current scanning, and it consists of a number of samples. The processing of a high number of samples requires computation resources that are than those ones available through actual embedded systems and also long data transfer sessions towards a centralized logging system. In this paper an algorithm which does not need any prior knowledge about the module, but which is able to identify the main features from the current vs. voltage curve of the module thereof is presented. The solutions presented in this paper overcome some limitations shown by an algorithm recently presented in literature. The results are validated by using simulated as well as experimental curves.
一种光伏组件主要特征识别的自适应方法
通过光伏组件的电流与电压曲线来识别其主要特征是许多应用的主要兴趣,例如诊断和动态重构。事实上,自动检测它在不匹配的条件下工作的事实,或者一些与它的健康状况直接相关的数据将非常有用。该曲线通常由开关变换器获得,执行电压/电流扫描,它由许多样本组成。处理大量样本所需的计算资源比实际嵌入式系统所能提供的计算资源要多,而且向集中式日志系统传输数据的会话也很长。本文提出了一种不需要对模块有任何先验知识,而能从模块的电流电压曲线中识别出主要特征的算法。本文提出的解决方案克服了最近文献中提出的一种算法所显示的一些局限性。用仿真曲线和实验曲线对结果进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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