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Scoping the potential usefulness of seasonal climate forecasts for solar power management

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  • De Felice, Matteo
  • Soares, Marta Bruno
  • Alessandri, Andrea
  • Troccoli, Alberto

Abstract

Solar photovoltaic energy is widespread worldwide and particularly in Europe, which became in 2016 the first region in the world to pass the 100 GW of installed capacity. As with all the renewable energy sources, for an effective management of solar power, it is essential to have reliable and accurate information about weather/climate conditions that affect the production of electricity. Operations in the solar energy industry are normally based on daily (or intra-daily) forecasts. Nevertheless, information about the incoming months can be relevant to support and inform operational and maintenance activities.

Suggested Citation

  • De Felice, Matteo & Soares, Marta Bruno & Alessandri, Andrea & Troccoli, Alberto, 2019. "Scoping the potential usefulness of seasonal climate forecasts for solar power management," Renewable Energy, Elsevier, vol. 142(C), pages 215-223.
    • Handle: RePEc:eee:renene:v:142:y:2019:i:c:p:215-223
    DOI: 10.1016/j.renene.2019.03.134
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    References listed on IDEAS

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    1. De Felice, Matteo & Petitta, Marcello & Ruti, Paolo M., 2015. "Short-term predictability of photovoltaic production over Italy," Renewable Energy, Elsevier, vol. 80(C), pages 197-204.
    2. Mavromatakis, F. & Makrides, G. & Georghiou, G. & Pothrakis, A. & Franghiadakis, Y. & Drakakis, E. & Koudoumas, E., 2010. "Modeling the photovoltaic potential of a site," Renewable Energy, Elsevier, vol. 35(7), pages 1387-1390.
    3. Marta Bruno Soares & Suraje Dessai, 2016. "Barriers and enablers to the use of seasonal climate forecasts amongst organisations in Europe," Climatic Change, Springer, vol. 137(1), pages 89-103, July.
    4. Brayshaw, David James & Troccoli, Alberto & Fordham, Rachael & Methven, John, 2011. "The impact of large scale atmospheric circulation patterns on wind power generation and its potential predictability: A case study over the UK," Renewable Energy, Elsevier, vol. 36(8), pages 2087-2096.
    5. De Felice, Matteo & Alessandri, Andrea & Catalano, Franco, 2015. "Seasonal climate forecasts for medium-term electricity demand forecasting," Applied Energy, Elsevier, vol. 137(C), pages 435-444.
    6. Boilley, Alexandre & Wald, Lucien, 2015. "Comparison between meteorological re-analyses from ERA-Interim and MERRA and measurements of daily solar irradiation at surface," Renewable Energy, Elsevier, vol. 75(C), pages 135-143.
    7. Maria Carmen Lemos & Christine J. Kirchhoff & Vijay Ramprasad, 2012. "Narrowing the climate information usability gap," Nature Climate Change, Nature, vol. 2(11), pages 789-794, November.
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    Cited by:

    1. D’Isidoro, Massimo & Briganti, Gino & Vitali, Lina & Righini, Gaia & Adani, Mario & Guarnieri, Guido & Moretti, Lorenzo & Raliselo, Muso & Mahahabisa, Mabafokeng & Ciancarella, Luisella & Zanini, Gabr, 2020. "Estimation of solar and wind energy resources over Lesotho and their complementarity by means of WRF yearly simulation at high resolution," Renewable Energy, Elsevier, vol. 158(C), pages 114-129.
    2. Lledó, Llorenç & Ramon, Jaume & Soret, Albert & Doblas-Reyes, Francisco-Javier, 2022. "Seasonal prediction of renewable energy generation in Europe based on four teleconnection indices," Renewable Energy, Elsevier, vol. 186(C), pages 420-430.

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