Irradiance prediction using Echo State Queueing Networks and Differential polynomial Neural Networks
Sebastián Basterrech, Ladislav Zjavka, Lukáš Prokop, Stanislav Mišák · 2013
This paper investigates the estimation of a real time-series benchmark: the solar irradiance forcasting. The global solar irradiance is an important variable in the production of renewable energy sources. These variable is very unstable and hard to be predicted. For the prediction, we use two new models for time-series modeling: Echo State Queueing Networks and Differential polynomial Neural Networks. Both tools have been proven to be efficient for forecasting and time-series modeling. We compare their performances for this particular data set.