Real-time Simulation of Photovoltaic Arrays by Growing Neural Gas Controlled DC-DC Converter (Contributo in atti di convegno)

Type

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

Label

• Real-time Simulation of Photovoltaic Arrays by Growing Neural Gas Controlled DC-DC Converter (Contributo in atti di convegno) (literal)

Anno

• 2008-01-01T00:00:00+01:00 (literal)

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

• 10.1109/PESC.2008.4592238 (literal)

Alternative label

• M. Cirrincione, M. C. Di Piazza, M. Pucci, G. Vitale (2008)
  Real-time Simulation of Photovoltaic Arrays by Growing Neural Gas Controlled DC-DC Converter
  in 39th IEEE Power Electronics Specialist Conference PESC 08, June 15-19, 2008, Rhodes, Greece
  (literal)

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

• M. Cirrincione, M. C. Di Piazza, M. Pucci, G. Vitale (literal)

Pagina inizio

• 2004 (literal)

Pagina fine

• 2010 (literal)

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

• http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=4592238&url=http%3A%2F%2Fieeexplore.ieee.org%2Fstamp%2Fstamp.jsp%3Ftp%3D%26arnumber%3D4592238 (literal)

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

• Conference proceedings (IEEE Power Electron. Specialists Conf.) (literal)

Rivista

• Conference proceedings (Rivista)

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

• 6 (literal)

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

• This paper presents a real-time simulator of a photovoltaic array based on a Growing Neural Gas (GNG) controlled DC-DC buck converter circuit. The DC-DC converter, driven by the current-voltage-irradiance-temperature mapping supplied by the GNG, is able to accurately describe the set of characteristics of a PV array, including their dependence on the solar irradiance and the cell temperature. A voltage linear closed loop control of the DC-DC converter has been done. The stability of the system in the discrete domain has been proven in all load conditions. A prototype of the GNG based PV emulator has been designed and set up both in its hardware and software part. The experimental implementation of the PV input-output mapping, based on the GNG network, has been done on a DSP-2 board. Results show a good agreement between the theoretical characteristics of the PV and the simulated and experimental ones in all tested working conditions. Particularly, the GNG network has correctly learnt the PV characteristics in the 4-dimensional space and is able to distinguish in production phase the different temperature and irradiance conditions. Also transient tests show a correct and stable transition between different points of the same characteristic or points of different characteristics. (literal)

Note

• ISI Web of Science (WOS) (literal)
• Scopus (literal)

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

• I.S.S.I.A.-C.N.R. (Institute on Intelligent Systems for the Automation), Palermo – Italy (literal)

Titolo

• Real-time Simulation of Photovoltaic Arrays by Growing Neural Gas Controlled DC-DC Converter (literal)

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

• 978-1-4244-1666-0 (literal)

Abstract

• This paper presents a real-time simulator of a photovoltaic array based on a Growing Neural Gas (GNG) controlled DC-DC buck converter circuit. The DC-DC converter, driven by the current-voltage-irradiance-temperature mapping supplied by the GNG, is able to accurately describe the set of characteristics of a PV array, including their dependence on the solar irradiance and the cell temperature. A voltage linear closed loop control of the DC-DC converter has been done. The stability of the system in the discrete domain has been proven in all load conditions. A prototype of the GNG based PV emulator has been designed and set up both in its hardware and software part. The experimental implementation of the PV input-output mapping, based on the GNG network, has been done on a DSP-2 board. Results show a good agreement between the theoretical characteristics of the PV and the simulated and experimental ones in all tested working conditions. Particularly, the GNG network has correctly learnt the PV characteristics in the 4-dimensional space and is able to distinguish in production phase the different temperature and irradiance conditions. Also transient tests show a correct and stable transition between different points of the same characteristic or points of different characteristics. (literal)

Prodotto di

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

Autore CNR

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

Insieme di parole chiave

• Parole chiave di "Real-time Simulation of Photovoltaic Arrays by Growing Neural Gas Controlled DC-DC Converter" (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)

Autore CNR di

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

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

• Conference proceedings (Rivista)

Insieme di parole chiave di

• Parole chiave di "Real-time Simulation of Photovoltaic Arrays by Growing Neural Gas Controlled DC-DC Converter" (Insieme di parole chiave)