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Accurate thermal prediction model for building-integrated photovoltaics systems using guided artificial intelligence algorithms

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  • Serrano-Luján, L.
  • Toledo, C.
  • Colmenar, J.M.
  • Abad, J.
  • Urbina, A.

Abstract

Progress in development of building-integrated photovoltaic systems is still hindered by the complexity of the physics and materials properties of the photovoltaic (PV) modules and its effect on the thermal behavior of the building. This affects not only the energy generation, as its active function and linked to economic feasibility, but also the thermal insulation of the building as part of the structure’s skin. Traditional modeling methods currently presents limitations, including the fact that they do not account for material thermal inertia and that the proposed semi-empirical coefficients do not define all types of technologies, mounting configuration, or climatic conditions. This article presents an artificial intelligence-based approach for predicting the temperature of a poly-crystalline silicon PV module based on local outdoor weather conditions (ambient temperature, solar irradiation, relative outdoor humidity and wind speed) and indoor comfort parameters (indoor temperature and indoor relative humidity) as inputs. A combination of two algorithms (Grammatical Evolution and Differential Evolution) guides to the creation of a customized expression based on the Sandia model. Different data-sets for a fully integrated PV system were tested to demonstrate its performance on three different types of days: sunny, cloudy and diffuse, showing relative errors of less than 4% in all cases and including night time. In comparison to Sandia model, this method reduces the error by up to 11% in conditions of variability of sky over short time intervals (cloudy days).

Suggested Citation

  • Serrano-Luján, L. & Toledo, C. & Colmenar, J.M. & Abad, J. & Urbina, A., 2022. "Accurate thermal prediction model for building-integrated photovoltaics systems using guided artificial intelligence algorithms," Applied Energy, Elsevier, vol. 315(C).
  • Handle: RePEc:eee:appene:v:315:y:2022:i:c:s0306261922004226
    DOI: 10.1016/j.apenergy.2022.119015
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    1. Siyuan Fan & Shengxian Cao & Yanhui Zhang, 2020. "Temperature Prediction of Photovoltaic Panels Based on Support Vector Machine with Pigeon-Inspired Optimization," Complexity, Hindawi, vol. 2020, pages 1-12, December.
    2. Chatzipanagi, Anatoli & Frontini, Francesco & Virtuani, Alessandro, 2016. "BIPV-temp: A demonstrative Building Integrated Photovoltaic installation," Applied Energy, Elsevier, vol. 173(C), pages 1-12.
    3. Alonso García, M.C. & Balenzategui, J.L., 2004. "Estimation of photovoltaic module yearly temperature and performance based on Nominal Operation Cell Temperature calculations," Renewable Energy, Elsevier, vol. 29(12), pages 1997-2010.
    4. Trinuruk, Piyatida & Sorapipatana, Chumnong & Chenvidhya, Dhirayut, 2009. "Estimating operating cell temperature of BIPV modules in Thailand," Renewable Energy, Elsevier, vol. 34(11), pages 2515-2523.
    5. Assoa, Ya Brigitte & Gaillard, Leon & Ménézo, Christophe & Negri, Nicolas & Sauzedde, François, 2018. "Dynamic prediction of a building integrated photovoltaic system thermal behaviour," Applied Energy, Elsevier, vol. 214(C), pages 73-82.
    6. A. Bassam & O. May Tzuc & M. Escalante Soberanis & L. J. Ricalde & B. Cruz, 2017. "Temperature Estimation for Photovoltaic Array Using an Adaptive Neuro Fuzzy Inference System," Sustainability, MDPI, vol. 9(8), pages 1-16, August.
    7. Dong Eun Jung & Chanuk Lee & Kee Han Kim & Sung Lok Do, 2020. "Development of a Predictive Model for a Photovoltaic Module’s Surface Temperature," Energies, MDPI, vol. 13(15), pages 1-18, August.
    8. D'Orazio, M. & Di Perna, C. & Di Giuseppe, E., 2014. "Experimental operating cell temperature assessment of BIPV with different installation configurations on roofs under Mediterranean climate," Renewable Energy, Elsevier, vol. 68(C), pages 378-396.
    9. Skoplaki, E. & Palyvos, J.A., 2009. "Operating temperature of photovoltaic modules: A survey of pertinent correlations," Renewable Energy, Elsevier, vol. 34(1), pages 23-29.
    10. Hassanien, Reda Hassanien Emam & Li, Ming & Dong Lin, Wei, 2016. "Advanced applications of solar energy in agricultural greenhouses," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 989-1001.
    11. Enescu, Diana, 2017. "A review of thermal comfort models and indicators for indoor environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1353-1379.
    12. Carlos Toledo & Lucía Serrano-Lujan & Jose Abad & Antonio Lampitelli & Antonio Urbina, 2019. "Measurement of Thermal and Electrical Parameters in Photovoltaic Systems for Predictive and Cross-Correlated Monitorization," Energies, MDPI, vol. 12(4), pages 1-20, February.
    13. Colmenar, J.M. & Hidalgo, J.I. & Salcedo-Sanz, S., 2018. "Automatic generation of models for energy demand estimation using Grammatical Evolution," Energy, Elsevier, vol. 164(C), pages 183-193.
    14. Yano, Akira & Cossu, Marco, 2019. "Energy sustainable greenhouse crop cultivation using photovoltaic technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 116-137.
    15. Carlos Toledo & Ana Maria Gracia Amillo & Giorgio Bardizza & Jose Abad & Antonio Urbina, 2020. "Evaluation of Solar Radiation Transposition Models for Passive Energy Management and Building Integrated Photovoltaics," Energies, MDPI, vol. 13(3), pages 1-24, February.
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