Application of DBN for estimating daily solar radiation on horizontal surfaces in Lhasa, China. (February 2019) - Wang, Miaomiao; Zang, Haixiang; Cheng, Lilin; Wei, Zhinong; Sun, Guoqiang
Abstract: The need of daily solar radiation (DSR) has been well recognized over the years because many countries consider solar energy into power grids. The essence of this paper is to apply the deep belief network (DBN) to estimating daily solar radiation on horizontal surfaces for Lhasa in China. Measured weather data (wind speed, sunshine duration, air dry-bulb temperature, air relative humidity) which cover the period of 1994–2015 are obtained and devoted to modeling. The statistical indicators (mean absolute bias error (MABE), root mean square error (RMSE) and correlation coefficient (R)) show that, the DBN model, optimized by testing the effect of multiple parameters, has more promising result when compared to back propagation (BP) network.