The traditional Power Grid has been designed in a hierarchical fashion, with Energy pushed from the large scale production facilities towards the end users. But with the increasing availability of micro and medium scale generating facilities, the situation is changing. Many end users can now produce energy and share it over the Power Grid. Naturally, end users need to have incentives to do so and might want to be able to act in an open decentralized energy market. In the present work, we offer a novel analysis of the Medium and Low Voltage Power Grids of the North Netherlands using statistical tools from the Complex Network Analysis field. We use a weighted model based on actual Grid data and propose a set of statistical measures to evaluate the adequacy of the current infrastructure for a decentralized energy market. Further, we use the insight gained by the analysis to propose parameters that tie the statistical topological measures to economic factors that might influence the attractiveness to the end users in participating in such a decentralized energy market, thus identifying what are the important topological parameters to work on to facilitate such open decentralized markets.
A different model is presented by Chassin @cite_37 where the analysis focuses on the North American Power Grid. The authors start with the hypothesis that the Grid can be modelled as a Scale-free network. This work is extremely relevant for the large size of the sample analysed (more than 300000 nodes) and the use of reliability measures that are typical of power engineering (e.g., loss of load probability) to quantify the failure characteristics of the network from a topological point of view. The similarity of the results obtained by considering reliability with authors' topological measures and other non topological studies for electrical Grids is interesting. However, a study of betweenness is unfortunately missing. Given the size of the sample (although it is not explicitly stated if components are considered or not) it would have useful to compute the betweenness of the nodes in order to understand if and how the betweenness behaves in this sort of big sample.
@cite_37
1972716516 2025761485 1571113954 1999647190
Numerous recent papers have found important relationships between network structure and risks within networks. These results indicate that network structure can dramatically affect the relative effectiveness of risk identification and mitigation methods. With this in mind this paper provides a comparative analysis of the topological and electrical structure of the IEEE 300 bus and the Eastern United States power grids. Specifically we compare the topology of these grids with that of random [1], preferential-attachment [2] and small-world [3] networks of equivalent sizes and find that power grids differ substantially from these abstract models in degree distribution, clustering, diameter and assortativity, and thus conclude that these abstract models do not provide substantial utility for modeling power grids. To better represent the topological properties of power grids we introduce a new graph generating algorithm, the minimum distance graph, that produces networks with properties that more nearly match those of known power grids. While these topological comparisons are useful, they do not account for the physical laws that govern flows in electricity networks. To elucidate the electrical structure of power grids, we propose a new method for representing electrical structure as a weighted graph. This analogous representation is based on electrical distance rather than topological connections. A comparison of these two representations of the test power grids reveals dramatic differences between the electrical and topological structure of electrical power systems. In this article, we model electric power delivery networks as graphs, and conduct studies of two power transmission grids, i.e., the Nordic and the western states (U.S.) transmission grid. We calculate values of topological (structural) characteristics of the networks and compare their error and attack tolerance (structural vulnerability), i.e., their performance when vertices are removed, with two frequently used theoretical reference networks (the Erdos-Renyi random graph and the Barabasi-Albert scale-free network). Further, we perform a structural vulnerability analysis of a fictitious electric power network with simple structure. In this analysis, different strategies to decrease the vulnerability of the system are evaluated. Finally, we present a discussion on the practical applicability of graph modeling. The topological (graph) structure of complex networks often provides valuable information about the performance and vulnerability of the network. However, there are multiple ways to represent a given network as a graph. Electric power transmission and distribution networks have a topological structure that is straightforward to represent and analyze as a graph. However, simple graph models neglect the comprehensive connections between components that result from Ohm's and Kirchhoff's laws. This paper describes the structure of the three North American electric power interconnections, from the perspective of both topological and electrical connectivity. We compare the simple topology of these networks with that of random, preferential-attachment, and small-world networks of equivalent sizes and find that power grids differ substantially from these abstract models in degree distribution, clustering, diameter and assortativity, and thus conclude that these topological forms may be misleading as models of power systems. To study the electrical connectivity of power systems, we propose a new method for representing electrical structure using electrical distances rather than geographic connections. Comparisons of these two representations of the North American power networks reveal notable differences between the electrical and topological structures of electric power networks. The reliability of electric transmission systems is examined using a scale-free model of network topology and failure propagation. The topologies of the North American eastern and western electric grids are analyzed to estimate their reliability based on the Barabasi–Albert network model. A commonly used power system reliability index is computed using a simple failure propagation model. The results are compared to the values of power system reliability indices previously obtained using standard power engineering methods, and they suggest that scale-free network models are usable to estimate aggregate electric grid reliability.