Assessing European power grid reliability by means of topological measures

Rosas-Casals, Martí; Corominas-Murtra, Bernat

doi:10.2495/esu090471

Cited by 29 publications

(44 citation statements)

References 16 publications

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“…If we compare the absolute numbers of the Big Data examples that we have analyzed in Section II, then there is no competition with the annual amount of data generated by social media or video repositories. However, to make the comparison fair considering Facebook, for example, if we account the the traffic generated by the more than 8 millions Dutch users of Facebook, 8 they are responsible for about 1.6 petabytes a year. We indeed note that the amount of data produced by the future Dutch smart grid is similar to the amount of data that the Dutch users produce each year on Facebook.…”

Section: Discussionmentioning

confidence: 99%

“…We consider the nodes (e.g., power and transformation station) since these contain the equipment and the sensors that monitor the status of the power assets and the lines. Considering the high voltage, the current number of nodes is provided in the work of Rosas-Casals and CorominasMurtra [8], whereas the information concerning the medium and low voltage nodes is provided by the various distribution utilities of the Netherlands. 5 For the high voltage grid, we consider a moderate evolution based on the public plans of the transmission operator (TenneT 6 ).…”

Section: A Volume and Velocitymentioning

confidence: 99%

See 1 more Smart Citation

The Smart Grid's Data Generating Potentials

Aiello¹,

Pagani²

2014

Annals of Computer Science and Information Systems

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Abstract-The Smart Grid is the vision underlying the evolution the power grid is currently undergoing. Its pillars are increased efficiency, self-healing, operation automation, and renewable energy integration obtained through real-time control and digitalization of the infrastructure. Thus, an important ingredient-if not the main one-is information technology support for power transmission and distribution. Given the size of the power grid, its pervasiveness, and the need for its availability, it is easy to imagine that any serious ICT infrastructure dealing with it will have to manage a great deal of rapidly forming data. Now the question is whether the amount, diversity, and uses of such data put the smart grid in the category of Big Data applications, followed by the natural question of what is the value of such data. To provide an initial answer to this question, we analyze the current state of data generation of the Dutch grid, its evolution towards a smart grid, and a future realistic scenario. The scenario considered shows that the amount of data generated is comparable to some of today's social media and "classic" Big Data examples.

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Section: Discussionmentioning

confidence: 99%

Section: A Volume and Velocitymentioning

confidence: 99%

The Smart Grid's Data Generating Potentials

Aiello¹,

Pagani²

2014

Annals of Computer Science and Information Systems

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show abstract

“…There are some selected papers [33,46,[86][87][88][89][90] that point out that CN science is a unifying, powerful technique that enables one to analyze, within the same conceptual framework, a great variety of very different systems whose constituent elements are organized in a networked way. The CN community, including part of the electrical engineering community [91], argue that the CN approach does not aim to reflect the detailed operation of a given grid, but to discover the possible emergence of a systemic or collective behavior, beyond that of its single components.…”

Section: Discussion: Is the Cn Approach Useful In Power Grids?mentioning

confidence: 99%

“…The review [33] points out that many works [46,86,89,90,105,106,[108][109][110][111][112] have in common that each power grid has been represented using the simplest graph model: undirected and unweighted. This is because these approaches do not include any characterization of the link weights.…”

Section: Unweighted and Weighted Graphs: Which Is The Best?mentioning

confidence: 99%

Optimizing the Structure of Distribution Smart Grids with Renewable Generation against Abnormal Conditions: A Complex Networks Approach with Evolutionary Algorithms

et al. 2017

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Abstract:In this work, we describe an approach that allows for optimizing the structure of a smart grid (SG) with renewable energy (RE) generation against abnormal conditions (imbalances between generation and consumption, overloads or failures arising from the inherent SG complexity) by combining the complex network (CN) and evolutionary algorithm (EA) concepts. We propose a novel objective function (to be minimized) that combines cost elements, related to the number of electric cables, and several metrics that quantify properties that are beneficial for SGs (energy exchange at the local scale and high robustness and resilience). The optimized SG structure is obtained by applying an EA in which the chromosome that encodes each potential network (or individual) is the upper triangular matrix of its adjacency matrix. This allows for fully tailoring the crossover and mutation operators. We also propose a domain-specific initial population that includes both small-world and random networks, helping the EA converge quickly. The experimental work points out that the proposed method works well and generates the optimum, synthetic, small-world structure that leads to beneficial properties such as improving both the local energy exchange and the robustness. The optimum structure fulfills a balance between moderate cost and robustness against abnormal conditions. Our approach should be considered as an analysis, planning and decision-making tool to gain insight into smart grid structures so that the low level detailed design is carried out by using electrical engineering techniques.

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“…What it does reveal is that fragility (measured by the undelivered energy and the total power loss) increases with γ, the parameter that characterizes the degree probability distribution [19]. From a structural point of view, increasing γ implies, rather counter-intuitively, a deviation towards more connected and not randomly topologies [156]. The authors conjecture that it seems as if the same criteria that favors connectivity (as a measure originally intended to avoid interruptions in power service) would simultaneously complicate the "islanding" of disturbances (preventing its spread).…”

Section: Topological Approachesmentioning

confidence: 99%

A Critical Review of Robustness in Power Grids Using Complex Networks Concepts

et al. 2015

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This paper reviews the most relevant works that have investigated robustness in power grids using Complex Networks (CN) concepts. In this broad field there are two different approaches. The first one is based solely on topological concepts, and uses metrics such as mean path length, clustering coefficient, efficiency and betweenness centrality, among many others. The second, hybrid approach consists of introducing (into the CN framework) some concepts from Electrical Engineering (EE) in the effort of enhancing the topological approach, and uses novel, more efficient electrical metrics such as electrical betweenness, net-ability, and others. There is however a controversy about whether these approaches are able to provide insights into all aspects of real power grids. The CN community argues that the topological approach does not aim to focus on the detailed operation, but to discover the unexpected emergence of collective behavior, while part of the EE community asserts that this leads to an excessive simplification. Beyond this open debate it seems to be no predominant structure (scale-free, small-world) in high-voltage transmission power grids, the vast majority of power grids studied so far. Most of them have in common that they are vulnerable to targeted attacks on the most connected nodes and robust to random failure. In this respect there are only a few works that propose strategies to improve robustness such as intentional islanding, restricted link addition, microgrids and Energies 2015, 8 9212 smart grids, for which novel studies suggest that small-world networks seem to be the best topology.

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Assessing European power grid reliability by means of topological measures

Cited by 29 publications

References 16 publications

The Smart Grid's Data Generating Potentials

The Smart Grid's Data Generating Potentials

Optimizing the Structure of Distribution Smart Grids with Renewable Generation against Abnormal Conditions: A Complex Networks Approach with Evolutionary Algorithms

A Critical Review of Robustness in Power Grids Using Complex Networks Concepts

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