Improving Model Chain Approaches for Probabilistic Solar Energy Forecasting through Post-processing and Machine Learning
N Horat, S Klerings, S Lerch - arXiv preprint arXiv:2406.04424, 2024 - arxiv.org
Weather forecasts from numerical weather prediction models play a central role in solar
energy forecasting, where a cascade of physics-based models is used in a model chain …
energy forecasting, where a cascade of physics-based models is used in a model chain …
Clustering-based spatial interpolation of parametric post-processing models
S Baran, M Lakatos - arXiv preprint arXiv:2401.14393, 2024 - arxiv.org
Since the start of the operational use of ensemble prediction systems, ensemble-based
probabilistic forecasting has become the most advanced approach in weather prediction …
probabilistic forecasting has become the most advanced approach in weather prediction …
Parametric post-processing of ensemble forecasts across multiple weather variables and resolutions
M Lakatos-Szabó - dea.lib.unideb.hu
Ensemble weather forecasting has emerged as a transformative approach in the field of
meteorology. By combining multiple runs of numerical weather prediction models, ensemble …
meteorology. By combining multiple runs of numerical weather prediction models, ensemble …
Machine learning-based parametric post-processing of solar irradiance ensemble forecasts
By the end of 2022, the renewable energy share of the global electricity capacity reached
40.3% and the new installations were dominated by solar energy, showing a global increase …
40.3% and the new installations were dominated by solar energy, showing a global increase …