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Generating low-voltage grid proxies in order to estimate grid capacity for residential end-use technologies: The case of residential solar PV
Due to data restrictions and power system complexity issues, it is difficult to estimate grid capacity for solar PV on regional or national scales. We here present a novel method for estimating low-voltage grid capacity for residential solar PV using publicly available data. High-resolution GIS data...
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/PMC8374675/ https://www.ncbi.nlm.nih.gov/pubmed/34434853 http://dx.doi.org/10.1016/j.mex.2021.101431 |
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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 | Due to data restrictions and power system complexity issues, it is difficult to estimate grid capacity for solar PV on regional or national scales. We here present a novel method for estimating low-voltage grid capacity for residential solar PV using publicly available data. High-resolution GIS data on demographics and dwelling dynamics is used to generate theoretical low-voltage grids. Simplified power system calculations are performed on the generated low-voltage grids to estimate residential solar PV capacity with a high temporal resolution. The method utilizes previous developments in reference network modelling and solar PV hosting capacity assessments. The method is demonstrated using datasets from Sweden, UK and Germany. Even though the method is designed to estimate residential solar PV grid capacity, the first block of the method can be utilized to estimate grid capacity or impacts from other residential end-use technologies, such as electric heating or electric vehicle charging. This method presents: • A method for estimating peak demand based on population density and dwelling type. • Generation of low-voltage grids based on peak demand. • Sizing of transformers and cables based on national low-voltage regulations and standards. |
format | Online Article Text |
id | pubmed-8374675 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-83746752021-08-24 Generating low-voltage grid proxies in order to estimate grid capacity for residential end-use technologies: The case of residential solar PV Hartvigsson, Elias Odenberger, Mikael Chen, Peiyuan Nyholm, Emil MethodsX Method Article Due to data restrictions and power system complexity issues, it is difficult to estimate grid capacity for solar PV on regional or national scales. We here present a novel method for estimating low-voltage grid capacity for residential solar PV using publicly available data. High-resolution GIS data on demographics and dwelling dynamics is used to generate theoretical low-voltage grids. Simplified power system calculations are performed on the generated low-voltage grids to estimate residential solar PV capacity with a high temporal resolution. The method utilizes previous developments in reference network modelling and solar PV hosting capacity assessments. The method is demonstrated using datasets from Sweden, UK and Germany. Even though the method is designed to estimate residential solar PV grid capacity, the first block of the method can be utilized to estimate grid capacity or impacts from other residential end-use technologies, such as electric heating or electric vehicle charging. This method presents: • A method for estimating peak demand based on population density and dwelling type. • Generation of low-voltage grids based on peak demand. • Sizing of transformers and cables based on national low-voltage regulations and standards. Elsevier 2021-06-30 /pmc/articles/PMC8374675/ /pubmed/34434853 http://dx.doi.org/10.1016/j.mex.2021.101431 Text en © 2021 The Authors. Published by Elsevier B.V. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Method Article Hartvigsson, Elias Odenberger, Mikael Chen, Peiyuan Nyholm, Emil Generating low-voltage grid proxies in order to estimate grid capacity for residential end-use technologies: The case of residential solar PV |
title | Generating low-voltage grid proxies in order to estimate grid capacity for residential end-use technologies: The case of residential solar PV |
title_full | Generating low-voltage grid proxies in order to estimate grid capacity for residential end-use technologies: The case of residential solar PV |
title_fullStr | Generating low-voltage grid proxies in order to estimate grid capacity for residential end-use technologies: The case of residential solar PV |
title_full_unstemmed | Generating low-voltage grid proxies in order to estimate grid capacity for residential end-use technologies: The case of residential solar PV |
title_short | Generating low-voltage grid proxies in order to estimate grid capacity for residential end-use technologies: The case of residential solar PV |
title_sort | generating low-voltage grid proxies in order to estimate grid capacity for residential end-use technologies: the case of residential solar pv |
topic | Method Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8374675/ https://www.ncbi.nlm.nih.gov/pubmed/34434853 http://dx.doi.org/10.1016/j.mex.2021.101431 |
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