摘要
提出基于递推最小二乘法和小波变换的逐日太阳辐射度预测模型,根据气象数据,对不同的气候条件按照相似的日类型进行分类;对不同的日类型,建立不同的预测模型。结果表明:在日类型基础上,建立的递推最小二乘法与小波变换模型具有较高预测精度,在日照较充足的晴天,其预测精度明显高于阴天及雨天的预测精度。
There is a function relation between the sun radiation and photovoltaic power, the daily solar radiation forecasting model by use of Reeursive Least Squares （RLS） and Wavelet Transform （WT） was proposed in this paper. According to the meteorological data, the day with different conditions is classified to different day types, then built different forecasting models for different day types based on the history measurement data. The simulation results showed that the forecasting error of the model based on day types is improved, and the forecasting precision in the sunny weather is higher than the cloudy and rainy days.
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2013年第3期433-438,共6页
Acta Energiae Solaris Sinica
基金
国家自然科学基金(50967001)
人力资源与社会保障部留学人员科技活动项目
关键词
太阳辐射度
递推最小二乘法
小波变换
日类型
sun radiation
recursive least squares （RLS）
wavelet transform （WT）
day types
