规范化(社会学)
预测技巧
预测验证
计算机科学
预测误差
计量经济学
小波变换
小波
光伏系统
数据挖掘
统计
数学
人工智能
工程类
社会学
电气工程
人类学
作者
Thị Ngọc Anh Nguyễn,Felix Müsgens
出处
期刊:Applied Energy
[Elsevier]
日期:2022-10-01
卷期号:323: 119603-119603
被引量:6
标识
DOI:10.1016/j.apenergy.2022.119603
摘要
In this paper, 180 papers on photovoltaic (PV) output forecasting were reviewed and a database of forecast errors was extracted for statistical analysis. The paper shows that among the forecast models, hybrid models are most likely to become the primary form of PV output forecasting in the future. The use of data processing techniques is positively correlated with the forecast quality, while the lengths of the forecast horizons and out-of-sample test sets have negative effects on the forecast accuracy. The paper also found that the use of data normalization, the wavelet transform, and the inclusion of clear sky index and numerical weather prediction variables are the most effective data processing techniques. Furthermore, the paper found some evidence of “cherry picking” in the reporting of errors and we recommend that the test sets be at least one year long to avoid any distortion in the performance of the models.
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