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A Complex Network Approach for the Estimation of the Energy Demand of Electric Mobility
We study how renewable energy impacts regional infrastructures considering the full deployment of electric mobility at that scale. We use the Sardinia Island in Italy as a paradigmatic case study of a semi-closed system both by energy and mobility point of view. Human mobility patterns are estimated...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5762725/ https://www.ncbi.nlm.nih.gov/pubmed/29321575 http://dx.doi.org/10.1038/s41598-017-17838-5 |
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author | Mureddu, Mario Facchini, Angelo Scala, Antonio Caldarelli, Guido Damiano, Alfonso |
author_facet | Mureddu, Mario Facchini, Angelo Scala, Antonio Caldarelli, Guido Damiano, Alfonso |
author_sort | Mureddu, Mario |
collection | PubMed |
description | We study how renewable energy impacts regional infrastructures considering the full deployment of electric mobility at that scale. We use the Sardinia Island in Italy as a paradigmatic case study of a semi-closed system both by energy and mobility point of view. Human mobility patterns are estimated by means of census data listing the mobility dynamics of about 700,000 vehicles, the energy demand is estimated by modeling the charging behavior of electric vehicle owners. Here we show that current renewable energy production of Sardinia is able to sustain the commuter mobility even in the theoretical case of a full switch from internal combustion vehicles to electric ones. Centrality measures from network theory on the reconstructed network of commuter trips allows to identify the most important areas (hubs) involved in regional mobility. The analysis of the expected energy flows reveals long-range effects on infrastructures outside metropolitan areas and points out that the most relevant unbalances are caused by spatial segregation between production and consumption areas. Finally, results suggest the adoption of planning actions supporting the installation of renewable energy plants in areas mostly involved by the commuting mobility, avoiding spatial segregation between consumption and generation areas. |
format | Online Article Text |
id | pubmed-5762725 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-57627252018-01-17 A Complex Network Approach for the Estimation of the Energy Demand of Electric Mobility Mureddu, Mario Facchini, Angelo Scala, Antonio Caldarelli, Guido Damiano, Alfonso Sci Rep Article We study how renewable energy impacts regional infrastructures considering the full deployment of electric mobility at that scale. We use the Sardinia Island in Italy as a paradigmatic case study of a semi-closed system both by energy and mobility point of view. Human mobility patterns are estimated by means of census data listing the mobility dynamics of about 700,000 vehicles, the energy demand is estimated by modeling the charging behavior of electric vehicle owners. Here we show that current renewable energy production of Sardinia is able to sustain the commuter mobility even in the theoretical case of a full switch from internal combustion vehicles to electric ones. Centrality measures from network theory on the reconstructed network of commuter trips allows to identify the most important areas (hubs) involved in regional mobility. The analysis of the expected energy flows reveals long-range effects on infrastructures outside metropolitan areas and points out that the most relevant unbalances are caused by spatial segregation between production and consumption areas. Finally, results suggest the adoption of planning actions supporting the installation of renewable energy plants in areas mostly involved by the commuting mobility, avoiding spatial segregation between consumption and generation areas. Nature Publishing Group UK 2018-01-10 /pmc/articles/PMC5762725/ /pubmed/29321575 http://dx.doi.org/10.1038/s41598-017-17838-5 Text en © The Author(s) 2017 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/. |
spellingShingle | Article Mureddu, Mario Facchini, Angelo Scala, Antonio Caldarelli, Guido Damiano, Alfonso A Complex Network Approach for the Estimation of the Energy Demand of Electric Mobility |
title | A Complex Network Approach for the Estimation of the Energy Demand of Electric Mobility |
title_full | A Complex Network Approach for the Estimation of the Energy Demand of Electric Mobility |
title_fullStr | A Complex Network Approach for the Estimation of the Energy Demand of Electric Mobility |
title_full_unstemmed | A Complex Network Approach for the Estimation of the Energy Demand of Electric Mobility |
title_short | A Complex Network Approach for the Estimation of the Energy Demand of Electric Mobility |
title_sort | complex network approach for the estimation of the energy demand of electric mobility |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5762725/ https://www.ncbi.nlm.nih.gov/pubmed/29321575 http://dx.doi.org/10.1038/s41598-017-17838-5 |
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