Review of Statistical and Analytical Degradation Models for Photovoltaic Modules and Systems as Well as Related Improvements
Review of Statistical and Analytical Degradation Models for Photovoltaic Modules and Systems as Well as Related Improvements
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DOI：
10.1109/jphotov.2018.2870532
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发表时间：
2018-11-01
影响因子：
3
通讯作者：
Topic, Marko
中科院分区：
文献类型：
--
作者：
Lindig, Sascha;Kaaya, Ismail;Topic, Marko
在这项工作中，我们研究了可用退化模型的实用方法及其在光伏（PV）模块和系统中的使用。一方面，模型的退化预测被描述为用于系统级退化的计算，其中退化模式是未知的，因此物理场不能通过使用分析模型来包含。因此，使用安装在意大利博尔扎诺的两个光伏系统作为案例研究，描述并应用了几种统计模型来计算性能损失。即，讨论了简单线性回归（SLR）、经典季节分解、Loess 季节和趋势分解（STL）、Holt-Winters 指数平滑和自回归积分移动平均（ARIMA）。性能损失结果表明 SLR 产生的结果具有最高的不确定性。相比之下，STL 和 ARIMA 的准确度最高，其中 STL 因其更容易实现而受到青睐。另一方面，如果在受控条件下可以获得光伏组件级别的监测数据，则可以应用分析模型。因此讨论了取决于不同退化模式的几种分析模型。对提出的腐蚀模型进行了比较研究。尽管所讨论的模型的结果与实验观察的解释一致，但观察到降解预测存在很大差异。最后，应用潜在诱导退化模型来模拟三个气候带中光伏系统最大功率的退化：高山（德国楚格峰）、海洋（西班牙大加那利岛）和干旱（以色列内盖夫）。正如预期的那样，干旱气候下的退化预计会更加严重。
In this work, we investigate practical approaches of available degradation models and their usage in photovoltaic (PV) modules and systems. On the one hand, degradation prediction of models is described for the calculation of degradation at system level where the degradation mode is unknown and hence the physics cannot be included by the use of analytical models. Several statistical models are thus described and applied for the calculation of the performance loss using as case study two PV systems, installed in Bolzano/Italy. Namely, simple linear regression (SLR), classical seasonal-decomposition, seasonal-and trend-decomposition using Loess (STL), Holt-Winters exponential smoothing and autoregressive integrated moving average (ARIMA) are discussed. The performance loss results show that SLR produces results with highest uncertainties. In comparison, STL and ARIMA perform with the highest accuracy, whereby STL is favored because of its easier implementation. On the other hand, if monitoring data at PV module level are available in controlled conditions, analytical models can be applied. Several analytical models depending on different degradations modes are thus discussed. A comparison study is carried out for models proposed for corrosion. Although the results of the models in question agree in explanation of experimental observations, a big difference in degradation prediction was observed. Finally, a model proposed for potential induced degradation was applied to simulate the degradation of PV systems maximum power in three climatic zones: alpine (Zugspitze, Germany), maritime (Gran Canaria, Spain), and arid (Negev, Israel). As expected, a more severe degradation is predicted for arid climates.