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The added value of combining solar irradiance data and forecasts: A probabilistic benchmarking exercise

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  • Lauret, Philippe
  • Alonso-Suárez, Rodrigo
  • Amaro e Silva, Rodrigo
  • Boland, John
  • David, Mathieu
  • Herzberg, Wiebke
  • Le Gall La Salle, Josselin
  • Lorenz, Elke
  • Visser, Lennard
  • van Sark, Wilfried
  • Zech, Tobias

Abstract

Despite the growing awareness in academia and industry of the importance of solar probabilistic forecasting for further enhancing the integration of variable photovoltaic power generation into electrical power grids, there is still no benchmark study comparing a wide range of solar probabilistic methods across various local climates. Having identified this research gap, experts involved in the activities of IEA PVPS T1611International Energy Agency - Photovoltaic Power Systems - Solar Resource for High Penetration and Large Scale Applications. agreed to establish a benchmarking exercise to evaluate the quality of intra-hour and intra-day probabilistic irradiance forecasts.

Suggested Citation

  • Lauret, Philippe & Alonso-Suárez, Rodrigo & Amaro e Silva, Rodrigo & Boland, John & David, Mathieu & Herzberg, Wiebke & Le Gall La Salle, Josselin & Lorenz, Elke & Visser, Lennard & van Sark, Wilfried, 2024. "The added value of combining solar irradiance data and forecasts: A probabilistic benchmarking exercise," Renewable Energy, Elsevier, vol. 237(PB).
    • Handle: RePEc:eee:renene:v:237:y:2024:i:pb:s0960148124016422
    DOI: 10.1016/j.renene.2024.121574
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