Model selection for accurate daily global solar radiation prediction in China

Abstract

Solar energy can share with a big percentage in solving in the environmental pollution and energy crisis in China. For the most application of solar energy, an accurate information of solar radiation amount received by a horizontal surface is the first step. In this study, nine-day of the year based models are calibrated and evaluated to estimate the daily global solar radiation (DGSR) on a horizontal surface using long-term data of 84 stations all over China. After dividing China into five solar climatic zones, the highest performance model for each zone is chosen to be a general day of the year based models and then calibrate and evaluated at each solar zone. Based on statistical indicator; the root mean square error (RMSE), the mean absolute bias error (MABE), coefficient of determination (R2) and the correlation coefficient (r) and the uncertainty based on a 95% confidence level (U95) and Taylor diagram, results show that the models perform best in the solar zones that receive a high amount of solar radiation and the performance decreases with decreasing of the daily solar radiation incidence. The hybrid sine and cosine wave day of the year based models exhibit the best performance, model D7 is the best for zone I and model D8 for zones II and IV. For zones II and V, the Gaussian form model (D3 model) and the 4th order polynomial model (D4 model) yield high performance, respectively. Whereas, the two Gaussian form model is the worth performance for all zones. The developed general day of the year based models for each zone in this study can be used with high accuracy to estimate the (DGSR) on a horizontal surface in areas where there is no data or the data is missing all over China.