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Solar irradiation from the energy production of residential PV systems

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  • Bertrand, Cédric
  • Housmans, Caroline
  • Leloux, Jonathan
  • Journée, Michel

Abstract

Considering the dense network of residential photovoltaic (PV) systems implemented in Belgium, the paper evaluates the opportunity of deriving global horizontal solar irradiation data from the electrical energy production registered at PV systems. The study is based on one year (i.e. 2014) of hourly PV power output collected at a representative sample of roughly 1500 residential PV installations. Validation is based on ground-based measurements of solar radiation performed within the network of radiometric stations operated by the Royal Meteorological Institute of Belgium and the method's performance is compared to the satellite-based retrieval approach.

Suggested Citation

  • Bertrand, Cédric & Housmans, Caroline & Leloux, Jonathan & Journée, Michel, 2018. "Solar irradiation from the energy production of residential PV systems," Renewable Energy, Elsevier, vol. 125(C), pages 306-318.
    • Handle: RePEc:eee:renene:v:125:y:2018:i:c:p:306-318
    DOI: 10.1016/j.renene.2018.02.036
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    References listed on IDEAS

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    1. Voyant, Cyril & Notton, Gilles & Kalogirou, Soteris & Nivet, Marie-Laure & Paoli, Christophe & Motte, Fabrice & Fouilloy, Alexis, 2017. "Machine learning methods for solar radiation forecasting: A review," Renewable Energy, Elsevier, vol. 105(C), pages 569-582.
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    1. Arsenio Barbón & Luis Bayón & Guzmán Díaz & Carlos A. Silva, 2022. "Investigation of the Effect of Albedo in Photovoltaic Systems for Urban Applications: Case Study for Spain," Energies, MDPI, vol. 15(21), pages 1-20, October.
    2. Gaigalis, Vygandas & Katinas, Vladislovas, 2020. "Analysis of the renewable energy implementation and prediction prospects in compliance with the EU policy: A case of Lithuania," Renewable Energy, Elsevier, vol. 151(C), pages 1016-1027.
    3. Osmani, Khaled & Haddad, Ahmad & Lemenand, Thierry & Castanier, Bruno & Ramadan, Mohamad, 2021. "An investigation on maximum power extraction algorithms from PV systems with corresponding DC-DC converters," Energy, Elsevier, vol. 224(C).
    4. Liu, Zhengguang & Guo, Zhiling & Chen, Qi & Song, Chenchen & Shang, Wenlong & Yuan, Meng & Zhang, Haoran, 2023. "A review of data-driven smart building-integrated photovoltaic systems: Challenges and objectives," Energy, Elsevier, vol. 263(PE).
    5. Guerrero-Lemus, R. & Cañadillas-Ramallo, D. & Reindl, T. & Valle-Feijóo, J.M., 2019. "A simple big data methodology and analysis of the specific yield of all PV power plants in a power system over a long time period," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 123-132.
    6. Gassar, Abdo Abdullah Ahmed & Cha, Seung Hyun, 2021. "Review of geographic information systems-based rooftop solar photovoltaic potential estimation approaches at urban scales," Applied Energy, Elsevier, vol. 291(C).

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