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      A Complex Network Approach for the Estimation of the Energy Demand of Electric Mobility

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          Abstract

          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.

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          Statistical mechanics of complex networks

          Complex networks describe a wide range of systems in nature and society, much quoted examples including the cell, a network of chemicals linked by chemical reactions, or the Internet, a network of routers and computers connected by physical links. While traditionally these systems were modeled as random graphs, it is increasingly recognized that the topology and evolution of real networks is governed by robust organizing principles. Here we review the recent advances in the field of complex networks, focusing on the statistical mechanics of network topology and dynamics. After reviewing the empirical data that motivated the recent interest in networks, we discuss the main models and analytical tools, covering random graphs, small-world and scale-free networks, as well as the interplay between topology and the network's robustness against failures and attacks.
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            Coordinated Charging of Plug-In Hybrid Electric Vehicles to Minimize Distribution System Losses

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              Vehicle-to-Grid Regulation Reserves Based on a Dynamic Simulation of Mobility Behavior

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                Author and article information

                Contributors
                4.facchini@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                10 January 2018
                10 January 2018
                2018
                : 8
                : 268
                Affiliations
                [1 ]ISNI 0000 0004 1755 3242, GRID grid.7763.5, University of Cagliari, ; Cagliari, Italy
                [2 ]ISNI 0000 0004 1790 9464, GRID grid.462365.0, IMT School for Advanced Studies Lucca, ; Piazza San Francesco 19, 55100 Lucca, Italy
                [3 ]GRID grid.472642.1, CRN Institute for Complex Systems, ; via dei Taurini 19, 00185 Rome, Italy
                [4 ]GRID grid.435910.a, London Institute for Mathematical Sciences, ; 35a South Street Mayfair, W1K 2XF London, UK
                [5 ]Linkalab, Complex Systems Computational Laboratory, Viale Elmas, 142 09122 Cagliari, Italy
                Author information
                http://orcid.org/0000-0002-3414-2686
                Article
                17838
                10.1038/s41598-017-17838-5
                5762725
                29321575
                e35b95df-0f87-4b65-9873-b573e21064a2
                © 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/.

                History
                : 18 July 2017
                : 21 November 2017
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