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.
Casals @cite_15 analyse the whole European and try to extract non-topological reliability measures investigating the topological properties of the network. The analysed is the end composed of almost 2800 nodes that span across the European continent. The assumption is that node degree distribution follows an exponential decay for every single network composing the European network, each one having a characteristic parameter that is related to the of the specific Grid. Although this study is based on relevant samples, but half of the considered Grids are small both in size and order (below 100 nodes). The most interesting aspect is the use of new indicators to assess network reliability, but, as the same authors explicitly state, these metrics need more test and a deeper study. As remarked for other works, there is no mention about using weights to characterize the edges in the networks.
@cite_15
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Publicat originalment a: WIT transactions on ecology and the environment, 2009, vol. 121, p. 527-537