%0 Journal Article
%T Characteristics of Solar Energy Distribution and Index Forecasting across the Eastern Hexi Corridor<br>河西走廊东部太阳能分布特征及指数预报
%A QIAN Li
%A LIN Shu
%A YANG Yonglong
%A LAN Xiaobo
%A YAN Guohua
%A <br>钱莉
%A 林纾
%A 杨永龙
%A 兰晓波
%A 闫国华
%J 资源科学
%D 2010
%I 
%X Spatial and temporal distributions of solar radiation over the eastern Hexi Corridor were examined using around 30a solar radiation time series and linear regression and correlation analysis. Results showed the average solar radiation was roughly 6166.2 MJ/m2 over the eastern Hexi Corridor. The average solar radiation showed a generally increasing trend, particularly since 1989. The year of solar radiation beginning to increase seemed to generally correspond to climate warming trends over this region. This suggested that the solar radiation over the Hexi corridor was essentially stable and somewhat increased in the context of global warming, which indeed provides favorable climate conditions for utilization of solar energy resources. The solar radiation had also obvious seasonal and monthly variations. Factors affecting solar radiation were analyzed with press (Prediction square sum) guidelines. The primary factors affecting solar radiation were found to be temperature, vapor pressure, relative humidity, specific humidity, temperature and dew point difference, and dew-point temperature. These factors were highly related to both the temperature which is capable of characterizing solar radiation intensity and the water vapor content in the atmosphere as well. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) numerical forecast products, a BP neural network prediction model for various months of daily solar radiation was established with the selected factors for optimal subset regression, with indexing its forecasting products. Preliminary results showed that the BP neural network prediction model is of strong capability to deal with non-linear mechanisms. This enables a better characterization of changes in solar radiation, suggesting the forecasting fitting rate and accuracy reaching a relatively high level. The business system docked with MICAPS, achieving full automation. This can produce weekly-based index forecasting of solar radiation, providing important technical support for precise forecasting of solar radiation and creating a new opportunity to realize meteorological index forecasting of solar radiation.
%K Solar radiation
%K Change characteristics
%K BP neural network
%K Solar energy index
%K Forecasting<br>太阳总辐射
%K 变化规律
%K BP神经网络
%K 太阳能指数
%K 预报
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=B5EDD921F3D863E289B22F36E70174A7007B5F5E43D63598017D41BB67247657&cid=B47B31F6349F979B&jid=9DEEAF23637E6E9539AD99BE6ABAB2B3&aid=29A7E04B869CB12996F324E12E63FBBD&yid=140ECF96957D60B2&vid=9971A5E270697F23&iid=59906B3B2830C2C5&sid=35ACD3314F0EF900&eid=BC035D350257EF96&journal_id=1007-7588&journal_name=资源科学&referenced_num=2&reference_num=16