ANN Based Model of PV Modules

  1. Jose Manuel Lopez-Guede 11
  2. Jose Antonio Ramos-Hernanz 1
  3. Manuel Graña 11
  4. Valeriu Ionescu 2
  1. 1 Universidad del País Vasco/Euskal Herriko Unibertsitatea
    info

    Universidad del País Vasco/Euskal Herriko Unibertsitatea

    Lejona, España

    ROR https://ror.org/000xsnr85

  2. 2 University of Pitesti
    info

    University of Pitesti

    Piteşti, Rumanía

    ROR https://ror.org/058b16x44

Libro:
International Joint Conference SOCO’16-CISIS’16-ICEUTE’16: San Sebastián, Spain, October 19th-21st, 2016 Proceedings
  1. Manuel Graña (coord.)
  2. José Manuel López-Guede (coord.)
  3. Oier Etxaniz (coord.)
  4. Álvaro Herrero (coord.)
  5. Héctor Quintián (coord.)
  6. Emilio Corchado (coord.)

Editorial: Springer Suiza

ISBN: 978-3-319-47364-2,  3-319-47364-6,  978-3-319-47363-5,  3-319-47363-8

Año de publicación: 2017

Páginas: 147-155

Congreso: International Conference on Computational Intelligence in Security for Information Systems (9. 2016. San Sebastián)

Tipo: Aportación congreso

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Resumen

In this paper authors address the practical problem of designing an empirical model for a commercial photovoltaic (PV) module (Mitsubishi PV-TD1185MF5) placed at the Faculty of Engineering of Vitoria (Basque Country University, Spain) based on artificial neural networks (ANN). This model obtains Ipv from Vpv, and the paper explains how the empirical data have been gathered and discusses the obtained results. The model reached an average accuracy of 0,15 A and a medium correlation value of R = 0,995.

Fuente de los datos: Dialnet