计算机科学
规范化(社会学)
预处理器
太阳能
统计模型
数据预处理
统计分析
数据挖掘
环境科学
统计
机器学习
人工智能
数学
工程类
电气工程
社会学
人类学
作者
Gang Su,Shuangyang Zhang,Wanxiang Yao,Mengru Hu,Haodong Hao
标识
DOI:10.1016/j.enbenv.2021.12.001
摘要
Diffuse solar radiation models play an extremely important role in solar photothermal utilization, resource assessment and energy consumption simulation, etc. The accuracy of these diffuse solar radiation models usually need to be evaluated by various statistical parameters. Among these statistical parameters, the Global Performance Index (GPI) has been extensively employed in recent years because of its comprehensiveness and wide applicability. This paper takes five cities in China as representatives of 5 typical climate regions, and 12 solar scattered radiation models are fitted with the meteorological data of 5 cities. Based on the comparative analysis of the existing GPI calculation methods, this paper points out that there are some defects in the existing GPI, and modifies the existing GPI based on the comprehensive consideration of statistical parameters, normalization preprocessing of statistical parameters, unified evaluation direction of parameters, weight redistribution of statistical parameters, and adjustment of extreme coefficient. 12 types of new GPI are established in this paper, and the performance of diffuse solar radiation models are compared based on these GPI. The rationality of GPI corrective measures is analyzed by means of the method reasonable index (MRI). The results show that the GPI calculation method (N10) which takes five corrective measures has the best performance, and the accuracy of the existing GPI can be improved by 13.33 to 65%.
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