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A harmonised, high-coverage, open dataset of solar photovoltaic installations in the UK
Solar photovoltaic (PV) is an increasingly significant fraction of electricity generation. Efficient management, and innovations such as short-term forecasting and machine vision, demand high-resolution geographic datasets of PV installations. However, official and public sources have notable defici...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666217/ https://www.ncbi.nlm.nih.gov/pubmed/33188212 http://dx.doi.org/10.1038/s41597-020-00739-0 |
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author | Stowell, Dan Kelly, Jack Tanner, Damien Taylor, Jamie Jones, Ethan Geddes, James Chalstrey, Ed |
author_facet | Stowell, Dan Kelly, Jack Tanner, Damien Taylor, Jamie Jones, Ethan Geddes, James Chalstrey, Ed |
author_sort | Stowell, Dan |
collection | PubMed |
description | Solar photovoltaic (PV) is an increasingly significant fraction of electricity generation. Efficient management, and innovations such as short-term forecasting and machine vision, demand high-resolution geographic datasets of PV installations. However, official and public sources have notable deficiencies: spatial imprecision, gaps in coverage and lack of crucial meta data, especially for small-scale solar panel installations. We present the results of a major crowd-sourcing campaign to create open geographic data for over 260,000 solar PV installations across the UK, covering an estimated 86% of the capacity in the country. We focus in particular on capturing small-scale domestic solar PV, which accounts for a significant fraction of generation but was until now very poorly documented. Our dataset suggests nameplate capacities in the UK (as of September 2020) amount to a total of 10.66 GW explicitly mapped, or 13.93 GW when missing capacities are inferred. Our method is applied to the UK but applicable worldwide, and compatible with continual updating to track the rapid growth in PV deployment. |
format | Online Article Text |
id | pubmed-7666217 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-76662172020-11-17 A harmonised, high-coverage, open dataset of solar photovoltaic installations in the UK Stowell, Dan Kelly, Jack Tanner, Damien Taylor, Jamie Jones, Ethan Geddes, James Chalstrey, Ed Sci Data Data Descriptor Solar photovoltaic (PV) is an increasingly significant fraction of electricity generation. Efficient management, and innovations such as short-term forecasting and machine vision, demand high-resolution geographic datasets of PV installations. However, official and public sources have notable deficiencies: spatial imprecision, gaps in coverage and lack of crucial meta data, especially for small-scale solar panel installations. We present the results of a major crowd-sourcing campaign to create open geographic data for over 260,000 solar PV installations across the UK, covering an estimated 86% of the capacity in the country. We focus in particular on capturing small-scale domestic solar PV, which accounts for a significant fraction of generation but was until now very poorly documented. Our dataset suggests nameplate capacities in the UK (as of September 2020) amount to a total of 10.66 GW explicitly mapped, or 13.93 GW when missing capacities are inferred. Our method is applied to the UK but applicable worldwide, and compatible with continual updating to track the rapid growth in PV deployment. Nature Publishing Group UK 2020-11-13 /pmc/articles/PMC7666217/ /pubmed/33188212 http://dx.doi.org/10.1038/s41597-020-00739-0 Text en © The Author(s) 2020 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 associated with this article. |
spellingShingle | Data Descriptor Stowell, Dan Kelly, Jack Tanner, Damien Taylor, Jamie Jones, Ethan Geddes, James Chalstrey, Ed A harmonised, high-coverage, open dataset of solar photovoltaic installations in the UK |
title | A harmonised, high-coverage, open dataset of solar photovoltaic installations in the UK |
title_full | A harmonised, high-coverage, open dataset of solar photovoltaic installations in the UK |
title_fullStr | A harmonised, high-coverage, open dataset of solar photovoltaic installations in the UK |
title_full_unstemmed | A harmonised, high-coverage, open dataset of solar photovoltaic installations in the UK |
title_short | A harmonised, high-coverage, open dataset of solar photovoltaic installations in the UK |
title_sort | harmonised, high-coverage, open dataset of solar photovoltaic installations in the uk |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666217/ https://www.ncbi.nlm.nih.gov/pubmed/33188212 http://dx.doi.org/10.1038/s41597-020-00739-0 |
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