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.
Highlights
In recent years energy production is experiencing a paradigm shift towards more clean and sustainable Renewable Energy Sources (RES)
The aim has been to guarantee the homogeneity of the possible power configurations both in the 33 and 69 bus cases, filtering in this way the impact of effects not strictly related with the network topology
To understand if batteries placed in the optimal position according to centrality metrics lead to positions that are optimal under the point of view of power flows, we studied the correlation properties between the computed nodes centrality and the interquartile difference Δq of the voltage fluctuation observed by placing the Energy Storage Systems (ESS) in each node
Summary
In recent years energy production is experiencing a paradigm shift towards more clean and sustainable Renewable Energy Sources (RES). Heuristic methods for finding the optimal location of the ESS in the networks with regards of voltage regulation, have been proposed by[7,16,17], but such approaches are limited by the size and topology of the the network, leading to results referred to specific case studies, while there is still the need for a criterion able to cope with complex and wide topologies, with low computational effort, and more accuracy. In this sense, using a multi-disciplinary approach bridging complex networks science and electrical engineering appears to be promising. Results show that there is a statistically significant correlation between the node eigenvector centrality and the optimal position of ESS, with a positive impacts on their voltage regulation abilities, and a overall reduction of the voltage fluctuations by a value up to 50%, significantly increasing the power quality
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