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Solar and wind forecasting by NARX neural networks

Conference Paper
Publication Date:
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.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Solar energy; wind energy; forecasting; neural networks; NARX
List of contributors:
Vitale, Gianpaolo; DI PIAZZA, MARIA CARMELA
Authors of the University:
DI PIAZZA MARIA CARMELA
VITALE GIANPAOLO
Handle:
https://iris.cnr.it/handle/20.500.14243/304527
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