Estimation of Daily Irradiation Exposure of Global Radiation Using Elman Neural Network

摘要

Using the data of three Meteorological Stations at Fushan, Ji'nan and Juxian, 2000–2003, the Elman neural network model was established to estimate the daily solar irradiance. The modeling results showed that a the three Meteorological Stations, the Mean Percentage Error (MPE) ranged from 17.3% to 21.3%, the Root Mean Square Error (RMSE) from 1.7 to 2.02 MJ·m-². The difference between the estimated and observed daily solar irradiance was smallest at Fushan Stations among the three Meteorological Stations, ranging from −2 to 4 MJ m^−2.The estimated daily solar irradiances were greatly affected by the weather conditions, which were more accurate under the clear weather than those in other weather. Compared with the generalized regression neural network modeling results, the MPE decreased by 9%-16% and the RMSE decreased by 0.506 MJ·m⁻²on average at the three Meteorological Stations.