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RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system

Future highly renewable energy systems will couple to complex weather and climate dynamics. This coupling is generally not captured in detail by the open models developed in the power and energy system communities, where such open models exist. To enable modeling such a future energy system, we desc...

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Detalles Bibliográficos
Autores principales: Jensen, Tue V., Pinson, Pierre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5706763/
https://www.ncbi.nlm.nih.gov/pubmed/29182600
http://dx.doi.org/10.1038/sdata.2017.175
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author Jensen, Tue V.
Pinson, Pierre
author_facet Jensen, Tue V.
Pinson, Pierre
author_sort Jensen, Tue V.
collection PubMed
description Future highly renewable energy systems will couple to complex weather and climate dynamics. This coupling is generally not captured in detail by the open models developed in the power and energy system communities, where such open models exist. To enable modeling such a future energy system, we describe a dedicated large-scale dataset for a renewable electric power system. The dataset combines a transmission network model, as well as information for generation and demand. Generation includes conventional generators with their technical and economic characteristics, as well as weather-driven forecasts and corresponding realizations for renewable energy generation for a period of 3 years. These may be scaled according to the envisioned degrees of renewable penetration in a future European energy system. The spatial coverage, completeness and resolution of this dataset, open the door to the evaluation, scaling analysis and replicability check of a wealth of proposals in, e.g., market design, network actor coordination and forecasting of renewable power generation.
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spelling pubmed-57067632017-12-01 RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system Jensen, Tue V. Pinson, Pierre Sci Data Data Descriptor Future highly renewable energy systems will couple to complex weather and climate dynamics. This coupling is generally not captured in detail by the open models developed in the power and energy system communities, where such open models exist. To enable modeling such a future energy system, we describe a dedicated large-scale dataset for a renewable electric power system. The dataset combines a transmission network model, as well as information for generation and demand. Generation includes conventional generators with their technical and economic characteristics, as well as weather-driven forecasts and corresponding realizations for renewable energy generation for a period of 3 years. These may be scaled according to the envisioned degrees of renewable penetration in a future European energy system. The spatial coverage, completeness and resolution of this dataset, open the door to the evaluation, scaling analysis and replicability check of a wealth of proposals in, e.g., market design, network actor coordination and forecasting of renewable power generation. Nature Publishing Group 2017-11-28 /pmc/articles/PMC5706763/ /pubmed/29182600 http://dx.doi.org/10.1038/sdata.2017.175 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.
spellingShingle Data Descriptor
Jensen, Tue V.
Pinson, Pierre
RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system
title RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system
title_full RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system
title_fullStr RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system
title_full_unstemmed RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system
title_short RE-Europe, a large-scale dataset for modeling a highly renewable European electricity system
title_sort re-europe, a large-scale dataset for modeling a highly renewable european electricity system
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5706763/
https://www.ncbi.nlm.nih.gov/pubmed/29182600
http://dx.doi.org/10.1038/sdata.2017.175
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