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Optimal positioning of storage systems in microgrids based on complex networks centrality measures
We propose a criterion based on complex networks centrality metrics to identify the optimal position of Energy Storage Systems in power networks. To this aim we study the relation between centrality metrics and voltage fluctuations in power grids in presence of high penetration of renewable energy s...
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/PMC6226440/ https://www.ncbi.nlm.nih.gov/pubmed/30413752 http://dx.doi.org/10.1038/s41598-018-35128-6 |
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author | Korjani, Saman Facchini, Angelo Mureddu, Mario Caldarelli, Guido Damiano, Alfonso |
author_facet | Korjani, Saman Facchini, Angelo Mureddu, Mario Caldarelli, Guido Damiano, Alfonso |
author_sort | Korjani, Saman |
collection | PubMed |
description | We propose a criterion based on complex networks centrality metrics to identify the optimal position of Energy Storage Systems in power networks. To this aim we study the relation between centrality metrics and voltage fluctuations in power grids in presence of high penetration of renewable energy sources and storage systems. For testing purposes we consider two prototypical IEEE networks and we compute the correlation between node centrality (namely Eigenvector, Closeness, Pagerank, Betweenness) and voltage fluctuations in presence of intermittent renewable energy generators and intermittent loads measured from domestic users. We show that the topological characteristics of the power networks are able to identify the optimal positioning of active and reactive power compensators (such as energy storage systems) used to reduce voltage fluctuations according to the common quality of service standards. Results show that, among the different metrics, eigenvector centrality shows a statistically significant exponential correlation with the reduction of voltage fluctuations. This finding confirms the technical know-how for which storage systems are heuristically positioned far from supply reactive nodes. This also represents an advantage both in terms of computational time, and in terms of planning of wide resilient networks, where a careful positioning of storage systems is needed, especially in a scenario of interconnected microgrids where intermittent distributed energy sources (such as wind or solar) are fully deployed. |
format | Online Article Text |
id | pubmed-6226440 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-62264402018-11-13 Optimal positioning of storage systems in microgrids based on complex networks centrality measures Korjani, Saman Facchini, Angelo Mureddu, Mario Caldarelli, Guido Damiano, Alfonso Sci Rep Article We propose a criterion based on complex networks centrality metrics to identify the optimal position of Energy Storage Systems in power networks. To this aim we study the relation between centrality metrics and voltage fluctuations in power grids in presence of high penetration of renewable energy sources and storage systems. For testing purposes we consider two prototypical IEEE networks and we compute the correlation between node centrality (namely Eigenvector, Closeness, Pagerank, Betweenness) and voltage fluctuations in presence of intermittent renewable energy generators and intermittent loads measured from domestic users. We show that the topological characteristics of the power networks are able to identify the optimal positioning of active and reactive power compensators (such as energy storage systems) used to reduce voltage fluctuations according to the common quality of service standards. Results show that, among the different metrics, eigenvector centrality shows a statistically significant exponential correlation with the reduction of voltage fluctuations. This finding confirms the technical know-how for which storage systems are heuristically positioned far from supply reactive nodes. This also represents an advantage both in terms of computational time, and in terms of planning of wide resilient networks, where a careful positioning of storage systems is needed, especially in a scenario of interconnected microgrids where intermittent distributed energy sources (such as wind or solar) are fully deployed. Nature Publishing Group UK 2018-11-09 /pmc/articles/PMC6226440/ /pubmed/30413752 http://dx.doi.org/10.1038/s41598-018-35128-6 Text en © The Author(s) 2018 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 Korjani, Saman Facchini, Angelo Mureddu, Mario Caldarelli, Guido Damiano, Alfonso Optimal positioning of storage systems in microgrids based on complex networks centrality measures |
title | Optimal positioning of storage systems in microgrids based on complex networks centrality measures |
title_full | Optimal positioning of storage systems in microgrids based on complex networks centrality measures |
title_fullStr | Optimal positioning of storage systems in microgrids based on complex networks centrality measures |
title_full_unstemmed | Optimal positioning of storage systems in microgrids based on complex networks centrality measures |
title_short | Optimal positioning of storage systems in microgrids based on complex networks centrality measures |
title_sort | optimal positioning of storage systems in microgrids based on complex networks centrality measures |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6226440/ https://www.ncbi.nlm.nih.gov/pubmed/30413752 http://dx.doi.org/10.1038/s41598-018-35128-6 |
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