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

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

Renewable Energy, 2024, vol. 237, issue PB

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.

Keywords: Probabilistic solar forecasting; Benchmarking exercise; Blended point forecast; CRPS; IEA PVPS T16 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:237:y:2024:i:pb:s0960148124016422

DOI: 10.1016/j.renene.2024.121574

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