Research On Solar Radiation Forecast In Wuhan Area Based On WRF

Recent years,with national economy has taken off,its national strength has become stronger,and energy consumption has also risen.Among the huge number of population in China,and its own energy resources are very scarce,and energy shortages have become increasingly serious.Therefore,renewable energy sources such as solar energy and wind energy are increasingly being valued and favored.Solar radiation is a very important green energy.The key prerequisite for effective use of solar energy is to master its spatial distribution characteristics and time rules.The thesis selects Wuhan City which is in Central of China as the research area to study the solar energy forecasting method based on WRF.Based on the observation data of Wu Han weather stations,ERA-interim of European Center for Mediumrange Weather Forecasts(ECMWF)reanalysis data and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model data,the thesis uses WRF model to predict the total solar radiation.In order to improve the accuracy of the WRF model for solar radiation prediction,the parametric schemes are tested in different combinations,and different terrain data are compared.The main conclusions are as follows:(1)Different combinations of parameterization schemes have great influence on solar radiation prediction.In the thesis,the sensitivity experiment of the parameterization scheme of solar radiation prediction based on WRF model in Wuhan area is carried out.The results show that: Thompson aerosol-aware + RRTM + Dudhia scheme + MM5 + Noah + Yonsei University scheme + Betts-Miller-Janjic scheme is the optimal parameterized conbination scheme,in which the simulated spatial resolution is3 km.The deviation between the solar radiation value of this scheme and the observation station data is 4.33,the average absolute percentage error is 86.27%,and the relative root mean square error is 161.75%.(2)Terrain data has a certain influence on solar radiation prediction.Replacing the default modis₂m terrain data with ASTER global digital elevation model data,under other conditions unchanged,the average absolute percentage error and relative root mean square error of the total solar radiation prediction has 5 %-10% improvement after the topographic data were replaced in January,April,July,and October(representing the four seasons of winter,spring,summer,and autumn respectively).(3)The matching degree of solar radiation prediction is higher in summer and autumn than in winter and spring.The overall radiation values are small in January.Rain and snow occupies most of the time,which has a greater impact on the forecast of solar radiation,making the forecast error the largest in January.Sunny is the main weather with days in July and October,and the overall radiation values fluctuate small,which also makes the solar radiation predicted by the WRF model better match the observation station data.The effect of WRF model simulation in different regions is closely related to parameterization schemes and topographic features.After determining the study area,choosing a suitable parameterization scheme and using high-precision topographic data make the simulation results of the WRF model more realistic and conducive to obtain better prediction results.