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.
2015
Istituto di Studi sui Sistemi Intelligenti per l'Automazione - ISSIA - Sede Bari
Solar energy
wind energy
forecasting
neural networks
NARX
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/304527
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