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Dataset for generating synthetic residential low-voltage grids in Sweden, Germany and the UK
Assessing grid capacity on national and local levels is important in order to formulate renewable energy targets, calculate integration costs of distributed generation (such as residential solar PV and electric vehicles). Currently, 70–96% of the residential solar PV installations in Germany and Ita...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8086020/ https://www.ncbi.nlm.nih.gov/pubmed/33981814 http://dx.doi.org/10.1016/j.dib.2021.107005 |
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author | Hartvigsson, Elias Odenberger, Mikael Chen, Peiyuan Nyholm, Emil |
author_facet | Hartvigsson, Elias Odenberger, Mikael Chen, Peiyuan Nyholm, Emil |
author_sort | Hartvigsson, Elias |
collection | PubMed |
description | Assessing grid capacity on national and local levels is important in order to formulate renewable energy targets, calculate integration costs of distributed generation (such as residential solar PV and electric vehicles). Currently, 70–96% of the residential solar PV installations in Germany and Italy are found in the low-voltage grid. Previous grid assessments have relied on grid data from individual low-voltage grids, making them limited to a few cases. This article presents synthetic low-voltage grid data from a reference network model. The reference network model generates synthetic low-voltage grids using publicly available data and national regulations and standards. In addition, the article presents data of residential solar photovoltaic hosting capacity in low-voltage grids. The datasets are high-resolution (1 × 1 km) and contains data on electricity peak demand, share of population living in apartments and important grid metrics such as transformer capacity, maximum feeder length and estimations of residential solar photovoltaic hosting capacity. Datasets on grid components are rare and the dataset can be used to assess grid impacts from other residential end-use technologies, and function as baseline for other reference network models. |
format | Online Article Text |
id | pubmed-8086020 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-80860202021-05-11 Dataset for generating synthetic residential low-voltage grids in Sweden, Germany and the UK Hartvigsson, Elias Odenberger, Mikael Chen, Peiyuan Nyholm, Emil Data Brief Data Article Assessing grid capacity on national and local levels is important in order to formulate renewable energy targets, calculate integration costs of distributed generation (such as residential solar PV and electric vehicles). Currently, 70–96% of the residential solar PV installations in Germany and Italy are found in the low-voltage grid. Previous grid assessments have relied on grid data from individual low-voltage grids, making them limited to a few cases. This article presents synthetic low-voltage grid data from a reference network model. The reference network model generates synthetic low-voltage grids using publicly available data and national regulations and standards. In addition, the article presents data of residential solar photovoltaic hosting capacity in low-voltage grids. The datasets are high-resolution (1 × 1 km) and contains data on electricity peak demand, share of population living in apartments and important grid metrics such as transformer capacity, maximum feeder length and estimations of residential solar photovoltaic hosting capacity. Datasets on grid components are rare and the dataset can be used to assess grid impacts from other residential end-use technologies, and function as baseline for other reference network models. Elsevier 2021-04-06 /pmc/articles/PMC8086020/ /pubmed/33981814 http://dx.doi.org/10.1016/j.dib.2021.107005 Text en © 2021 The Author(s). Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Hartvigsson, Elias Odenberger, Mikael Chen, Peiyuan Nyholm, Emil Dataset for generating synthetic residential low-voltage grids in Sweden, Germany and the UK |
title | Dataset for generating synthetic residential low-voltage grids in Sweden, Germany and the UK |
title_full | Dataset for generating synthetic residential low-voltage grids in Sweden, Germany and the UK |
title_fullStr | Dataset for generating synthetic residential low-voltage grids in Sweden, Germany and the UK |
title_full_unstemmed | Dataset for generating synthetic residential low-voltage grids in Sweden, Germany and the UK |
title_short | Dataset for generating synthetic residential low-voltage grids in Sweden, Germany and the UK |
title_sort | dataset for generating synthetic residential low-voltage grids in sweden, germany and the uk |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8086020/ https://www.ncbi.nlm.nih.gov/pubmed/33981814 http://dx.doi.org/10.1016/j.dib.2021.107005 |
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