Probabilistic solar forecasting: Benchmarks, post-processing, verification

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SEEK ID: https://publications.h-its.org/publications/1571

Filename: 2023SolarEnergy.pdf 

Format: PDF document

Size: 1.48 MB

SEEK ID: https://publications.h-its.org/publications/1571

DOI: 10.1016/j.solener.2022.12.054

Research Groups: Computational Statistics

Publication type: Journal

Journal: Solar Energy

Publisher: Elsevier BV

Citation: Solar Energy, 252:72–80

Date Published: 1st Mar 2023

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Registered Mode: manually

Authors: Tilmann Gneiting, Sebastian Lerch, Benedikt Schulz

Citation
Gneiting, T., Lerch, S., & Schulz, B. (2023). Probabilistic solar forecasting: Benchmarks, post-processing, verification. In Solar Energy (Vol. 252, pp. 72–80). Elsevier BV. https://doi.org/10.1016/j.solener.2022.12.054
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Created: 2nd Feb 2023 at 11:30

Last updated: 8th Mar 2024 at 13:53

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