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Application of Adaptive Models for the Determination of the Thermal Behaviour of a Photovoltaic Panel

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Computational Science and Its Applications – ICCSA 2013 (ICCSA 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7972))

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Abstract

The use of reliable forecasting models for the PV temperature is necessary for a more correct evaluation of energy and economic performances. Climatic conditions certainly have a remarkable influence on thermo-electric behaviour of the PV panel but the physical system is too complex for an analytical representation. A neural-network-based approach for solar panel temperature modelling is here presented. The models were trained using a set of data collected from a test facility. Simulation results of the trained neural networks are presented and compared with those obtained with an empirical correlation.

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Authors and Affiliations

  1. DEIM, Dipartimento di Energia, Ingegneria dell’informazione e Modelli matematici, Università di Palermo, viale delle scienze, Ed.9, 90128, Palermo, Italy

    Valerio Lo Brano, Giuseppina Ciulla & Marco Beccali

Authors
  1. Valerio Lo Brano
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  2. Giuseppina Ciulla
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  3. Marco Beccali
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Editor information

Editors and Affiliations

  1. L-I.S.U.T. - D.A.P.I.t. Facoltà Ingegneria, Università degli Studi della Basilicata, Viale dell’Ateneo Lucano, 10, 85100, Potenza, Italy

    Beniamino Murgante

  2. Covenant University, Canaanland, OTA, Nigeria

    Sanjay Misra

  3. Partimento di Scienze e Tecnologie per LAgricoltura, le Foreste, la Natura e lEnergia, Università degli Studi della Tuscia, Via S. Camillo de Lellis, snc, 01100, Viterbo, Italy

    Maurizio Carlini

  4. Dipartimento di Scienze dell’Ingegneria Civile e dell’Architecttura, Politecnico di Bari, Via Orabona, 4, 70125, Bari, Italy

    Carmelo M. Torre

  5. International University VNU-HCM, Quarter 6, Linh Trung, Thu Duc, Ho Chi Minh City, Vietnam

    Hong-Quang Nguyen

  6. School of Business Systems, Monash University, 3800, Clayton, VIC, Australia

    David Taniar

  7. Department of Intelligent Informatics, Kyushu Sangyo University, 2-3-1 Matsukadai, Higashi-ku, 813-8503, Fukuoka, Japan

    Bernady O. Apduhan

  8. Department of Mathematics and Computer Science, University of Perugia, Via Vanvitelli, 1, 06123, Perugia, Italy

    Osvaldo Gervasi

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Lo Brano, V., Ciulla, G., Beccali, M. (2013). Application of Adaptive Models for the Determination of the Thermal Behaviour of a Photovoltaic Panel. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2013. ICCSA 2013. Lecture Notes in Computer Science, vol 7972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39643-4_26

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  • DOI: https://doi.org/10.1007/978-3-642-39643-4_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39642-7

  • Online ISBN: 978-3-642-39643-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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