Predictability and forecast skill of solar irradiance over the contiguous United States

B Liu, D Yang, MJ Mayer, CFM Coimbra… - … and Sustainable Energy …, 2023 - Elsevier
Current solar forecast verification processes place much attention on performance
comparison of a group of competing methods. However, forecast verification ought to further …

Performance analysis of a solar based novel trigeneration system using cascaded vapor absorption-compression refrigeration system

Y Khan, RS Mishra - International Journal of Refrigeration, 2023 - Elsevier
Solar power tower technique has a strong potential among several solar systems for large-
scale power generation. It is crucial to make new, efficient trigeneration unit for solar power …

Non-crossing quantile regression neural network as a calibration tool for ensemble weather forecasts

M Song, D Yang, S Lerch, X Xia, GM Yagli… - … in Atmospheric Sciences, 2024 - Springer
Despite the maturity of ensemble numerical weather prediction (NWP), the resulting
forecasts are still, more often than not, under-dispersed. As such, forecast calibration tools …

Prediction of solar irradiance using convolutional neural network and attention mechanism-based long short-term memory network based on similar day analysis and …

X Hou, C Ju, B Wang - Heliyon, 2023 - cell.com
As one of the future's most promising clean energy sources, solar energy is the key to
developing renewable energy. The randomness of solar irradiance can affect the efficiency …

Comparison of model output statistics and neural networks to postprocess wind gusts

C Primo, B Schulz, S Lerch, R Hess - arXiv preprint arXiv:2401.11896, 2024 - arxiv.org
Wind gust prediction plays an important role in warning strategies of national meteorological
services due to the high impact of its extreme values. However, forecasting wind gusts is …

Uncertainty quantification for data-driven weather models

C Bülte, N Horat, J Quinting, S Lerch - arXiv preprint arXiv:2403.13458, 2024 - arxiv.org
Artificial intelligence (AI)-based data-driven weather forecasting models have experienced
rapid progress over the last years. Recent studies, with models trained on reanalysis data …

Decompositions of the mean continuous ranked probability score

S Arnold, EM Walz, J Ziegel, T Gneiting - arXiv preprint arXiv:2311.14122, 2023 - arxiv.org
The continuous ranked probability score (crps) is the most commonly used scoring rule in
the evaluation of probabilistic forecasts for real-valued outcomes. To assess and rank …

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

P Lauret, R Alonso-Suárez, RA e Silva, J Boland… - Renewable Energy, 2024 - Elsevier
Despite the growing awareness in academia and industry of the importance of solar
probabilistic forecasting for further enhancing the integration of variable photovoltaic power …

Probabilistic Solar Forecasts as a Binary Event Using a Sky Camera

M David, J Alonso-Montesinos, J Le Gal La Salle… - Energies, 2023 - mdpi.com
With the fast increase of solar energy plants, a high-quality short-term forecast is required to
smoothly integrate their production in the electricity grids. Usually, forecasting systems …

[HTML][HTML] Postprocessing of point predictions for probabilistic forecasting of day-ahead electricity prices: The benefits of using isotonic distributional regression

A Lipiecki, B Uniejewski, R Weron - Energy Economics, 2024 - Elsevier
Operational decisions relying on predictive distributions of electricity prices can result in
significantly higher profits compared to those based solely on point forecasts. However, the …