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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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    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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    3. Housmans, Caroline & Ipe, Alessandro & Bertrand, Cédric, 2017. "Tilt to horizontal global solar irradiance conversion: An evaluation at high tilt angles and different orientations," Renewable Energy, Elsevier, vol. 113(C), pages 1529-1538.
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    5. Haghdadi, Navid & Copper, Jessie & Bruce, Anna & MacGill, Iain, 2017. "A method to estimate the location and orientation of distributed photovoltaic systems from their generation output data," Renewable Energy, Elsevier, vol. 108(C), pages 390-400.
    6. Leloux, Jonathan & Narvarte, Luis & Trebosc, David, 2012. "Review of the performance of residential PV systems in France," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1369-1376.
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    2. 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).
    3. 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.
    4. 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.
    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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