将分解模型（decomposition model）按照输入参数、构造方法及特性分为3类,选择拉萨、西安、上海2016年辐射观测值作为实验数据,引入精确度分值（accuracy score, AS）作为模型适应性评判标准,研究晴、多云、阴3种天气类型下分解模型适应性规律以及针对不同天气类型适应模型形式。结果表明天气类型对模型的适应性有显著影响,即由晴到阴模型整体适应性呈下降趋势;当天气特别晴朗时第Ⅱ类模型适应性明显优于其他两类模型,而对于其他天气类型第Ⅰ类的C.P.R模型适应性最好。利用天气类型适应模型,3个地区全年逐时总辐射误差平均可减小3%,平均绝对误差百分率（PMAE）在20%~25%之间,均方根误差百分率（PRMSE）在26%~32%之间。可见利用天气适应模型能够有效减小估算误差,逐时总辐射数据精度能够满足建筑节能设计需求。
Abstract
This paper divides decomposition models into three categories according to input parameters, construction and characteristics. With the measured radiation data of Lhasa, Xi’an, and Shanghai in 2016, the adaptability of three types of models under three weather conditions of sunny, cloudy, and overcast days is compared and analyzed. Accuracy score（AS） is introduced as a standard to evaluate the model’s adaptability. The result shows that the weather condition significantly affects the adaptability of decomposition models,which decreases from sunny days to overcast days. When the weather is particularly sunny, models of category Ⅱ have a better adaptability than category Ⅰ and Ⅲ models. For other weather conditions, the C.P.R model from category Ⅰis the best. With the adaptive model, the error of hourly global radiation in three cities can be reduced by 3% on average, the percentage mean absolute error （PMAE）is between 20%-25%, and the percentage root mean square error （PRMSE）is between 26%-32%. In summary,using the weather adaptation model can effectively reduce errors and meet building energy-saving design requirements.
关键词
太阳辐射 /
逐时总辐射 /
天气类型 /
分解模型 /
精确度分值
Key words
solar radiation /
hourly global radiation /
weather type /
decomposition model /
accuracy score
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基金
国家自然科学基金重点项目（51838011）
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