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• W2900331492 abstract "Abstract 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." @default.
• W2900331492 created "2018-11-16" @default.
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• W2900331492 date "2018-11-09" @default.
• W2900331492 modified "2023-10-17" @default.
• W2900331492 title "Optimal positioning of storage systems in microgrids based on complex networks centrality measures" @default.
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• W2900331492 doi "https://doi.org/10.1038/s41598-018-35128-6" @default.
• W2900331492 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6226440" @default.
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