The nonlinear autoregressive network with exogenous input (NARX) is used to perform hourly solar irradiation and wind speed forecasting, according to a multi-step ahead approach. Temperature has been considered as the exogenous variable. The NARX topology selection is supported by a combined use of two techniques: 1. a genetic algorithm (GA)-based optimization technique and 2. a method that determines the optimal network architecture by pruning (Optimal Brain Surgeon (OBS) strategy). The considered variables are observed at hourly scale in a seven year dataset and the forecasting is done for several time horizons in the range from 8 to 24 hours-ahead.
Solar and wind forecasting by NARX neural networks
A Di Piazza;M C Di Piazza;G Vitale
2015
Abstract
The nonlinear autoregressive network with exogenous input (NARX) is used to perform hourly solar irradiation and wind speed forecasting, according to a multi-step ahead approach. Temperature has been considered as the exogenous variable. The NARX topology selection is supported by a combined use of two techniques: 1. a genetic algorithm (GA)-based optimization technique and 2. a method that determines the optimal network architecture by pruning (Optimal Brain Surgeon (OBS) strategy). The considered variables are observed at hourly scale in a seven year dataset and the forecasting is done for several time horizons in the range from 8 to 24 hours-ahead.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.