全球晴空辐照度模式的模式组合研究

Xixi Sun, Xiaoyi Yang, Peifeng Wang
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引用次数: 1

摘要

晴空全球水平辐照度(GHIcs)定义了达到水平表面的理论最大辐照度,通常来自半经验或基于物理的晴空模式。在这项研究中,我们提出了一种全球晴空模式的朴素模式组合方法,以改进GHIcs的估计。具体而言,从前人的研究[1]中选取10个表现最好的波束晴空模型和漫射晴空模型,配对创建97个全球晴空模型组合。通过包括18个独立的全球晴空模型(区别于单独的光束和漫射组合模型),本研究比较了全球100个太阳测量地面站下的115个全球晴空模型。经过严格的数据质量控制和晴空检测,使用1870万个1分钟时间数据点(2015年1月1日至2019年9月30日)来评估所有115个模型。然后采用主成分分析(PCA)排序程序对12个误差指标进行汇总,并给出总体排序分数。全球晴空模型全球性能排名前三的是MMAC-v1_IQBAL-C、MMAC-v2_PSIREST和REST2-v5,即不是最好的波束和漫射模型的组合。这样的结果可能是由于不同的光束和漫射模型估计过高或过低。另一个有趣的发现是REST2-v5模型,它在之前的研究中也被列为全球十大晴空模型之一。总的来说,大多数组合模型比原始模型获得了更高的性能(更高的PCA排名分数)。
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A Study of Models Combination for Global Clear Sky Irradiance Models
Clear sky global horizontal irradiance (GHIcs) defines the theoretical maximum irradiance reaching a horizontal surface and are often derived from semi-empirical or physical based clear-sky models. In this study we demonstrate a naive model combination method of global clear sky models for improved estimation of GHIcs. To be specific, 10 best performing beam and diffuse clear sky models are each selected from pervious study [1] and are paired to create 97 combinations of global clear-sky models. By including 18 standalone global clear sky models (distinguish from individual beam and diffuse combined models), this study compares 115 global clear sky models under 100 worldwide solar measurement ground stations. After rigorous data quality control and clear sky detection, 18.7 million 1-min time data points (between 2015-01-01 and 2019-09-30) are used to evaluate all 115 models. Principal Component Analysis (PCA) ranking procedure is then employed to aggregate 12 error metrics and provides the overall ranking scores. The top 3 world-wide performing global clear-sky models are MMAC-v1_IQBAL-C, MMAC-v2_PSIREST and REST2-v5, i.e., not the combination of the best beam and diffuse models. Such results may be due to the over- or under- estimation of different beam and diffuse models. Another interesting finding is the REST2-v5 model which was also listed in the top 10 global clear sky models in previous study. In all, most combined models achieve greater performance (higher PCA ranking scores) than the original ones.
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