Photovoltaic Solar Energy Laboratory, Unisinos Unversity, São Leopoldo - RS 93022-750, Brazil.
Centre Georges Peri, University of Corsica, 20000 Ajaccio, France.
Sensors (Basel). 2020 Apr 28;20(9):2490. doi: 10.3390/s20092490.
solar irradiance and cell temperature are the most significant aspects when assessing the production of a photovoltaic system. To avoid the need of specific sensors for quantifying such parameters, recent literature presents methods to estimate them through electrical measurements, using the photovoltaic module itself as a sensor. This work presents an application of such methods to data recorded using a research platform at University of Corsica, in France. The methods and the platform are briefly presented and the results are shown and discussed in terms of normalized mean absolute errors (nMAE) and root mean square errors (nRMSE) for various irradiance and cell temperature levels. The nMAE (and nRMSE) for solar irradiance are respectively between 3.5% and 3.9% (4.2% and 4.7%). Such errors on computed irradiance are in the same order of magnitude as those found in the literature, with a simple implementation. For cell temperatures estimation, the nMAE and nRMSE were found to be in the range 3.4%-8.2% and 4.3%-10.7%. These results show that using such methods could provide an estimation for the values of irradiance and cell temperature, even if the modules are not new and are not regularly cleaned, but of course not partially shaded.
在评估光伏系统的产量时,太阳辐照度和电池温度是最重要的方面。为了避免使用特定传感器来量化这些参数,最近的文献提出了通过电测量来估计这些参数的方法,使用光伏模块本身作为传感器。本工作将这些方法应用于在法国科西嘉岛大学的研究平台上记录的数据。简要介绍了这些方法和平台,并根据不同的辐照度和电池温度水平,以归一化平均绝对误差(nMAE)和均方根误差(nRMSE)的形式展示和讨论了结果。辐照度的 nMAE(和 nRMSE)分别在 3.5%到 3.9%(4.2%到 4.7%)之间。在具有简单实现的情况下,这种计算辐照度的误差与文献中的误差处于同一数量级。对于电池温度的估计,nMAE 和 nRMSE 的范围分别为 3.4%-8.2%和 4.3%-10.7%。这些结果表明,即使模块不是新的且未定期清洁,使用这种方法仍然可以提供辐照度和电池温度的估计值,但当然不能是部分阴影。