Solar radiation estimate and forecasting by neural networks for smart grid energy management (Contributo in atti di convegno)

Type

• Prodotto della ricerca (Classe)
• Contributo in atti di convegno (Classe)

Label

• Solar radiation estimate and forecasting by neural networks for smart grid energy management (Contributo in atti di convegno) (literal)

Anno

• 2013-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

• 10.4229/28thEUPVSEC2013-5BV.4.17 (literal)

Alternative label

• A. Di Piazza, M. C. Di Piazza and G. Vitale (2013)
  Solar radiation estimate and forecasting by neural networks for smart grid energy management
  in European PV Solar Energy Conference and Exhibition, Paris, France, 30 September - 04 October 2013
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• A. Di Piazza, M. C. Di Piazza and G. Vitale (literal)

Pagina inizio

• 3876 (literal)

Pagina fine

• 3881 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url

• https://www.eupvsec-proceedings.com/ (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume

• European PV Solar Energy Conference and Exhibition (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali

• 6 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• Consiglio Nazionale delle Ricerche (literal)

Titolo

• Solar radiation estimate and forecasting by neural networks for smart grid energy management (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn

• 3-936338-33-7 (literal)

Abstract

• The high rate of penetration of renewable energy in the context of smart grids and distributed generation makes the prediction of meteorological time series particularly useful for planning and management of the power grid with the aim of improving its overall efficiency and performance. On such a basis, this paper proposes an application of Artificial Neural Networks (ANNs) to the field of photovoltaic power generation. In particular, two suitably trained dynamic recurrent ANNs, i.e., the Focused Time-Delay Neural Network (FTDNN) and the Nonlinear autoregressive network with exogenous inputs (NARX), are used to develop a model for the estimate and forecast of daily solar radiation. ANNs implemented in this study show good performance since reliable and precise models of daily solar radiation, are obtained. This allows the PV output power for a given plant to be forecast as well. Finally, the potential of the proposed method in optimal sizing and energy management of electrical grids is outlined showing an example of NARX network application to electric load forecast. (literal)

Prodotto di

• Institute of intelligent systems for automation (ISSIA) (Istituto)
• Progetto Mezzogiorno_ISSIA (ET.P03.008.007) (Modulo)
• Convertitori, attuatori e azionamenti elettrici (SP.P03.011.001) (Modulo)

Autore CNR

• MARIA CARMELA DI PIAZZA (Persona)
• GIANPAOLO VITALE (Unità di personale interno)

Insieme di parole chiave

• Parole chiave di "Solar radiation estimate and forecasting by neural networks for smart grid energy management" (Insieme di parole chiave)

Incoming links:

Prodotto

• Institute of intelligent systems for automation (ISSIA) (Istituto)
• Convertitori, attuatori e azionamenti elettrici (SP.P03.011.001) (Modulo)
• Progetto Mezzogiorno_ISSIA (ET.P03.008.007) (Modulo)

Autore CNR di

• MARIA CARMELA DI PIAZZA (Persona)
• GIANPAOLO VITALE (Unità di personale interno)
• http://www.cnr.it/ontology/cnr/individuo/unitaDiPersonaleEsterno/ID23468

Insieme di parole chiave di

• Parole chiave di "Solar radiation estimate and forecasting by neural networks for smart grid energy management" (Insieme di parole chiave)