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DIAGNOSING VULNERABILITY, EMERGENT PHENOMENA, and VOLATILITY in MANMADE NETWORKS
WP2 Data CollationMANMADEMANMADECOLB, Budapest 21-22 of January 2008F. Bono, E. Gutierrez
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Data flow architecture*
Database
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Attributes of Data Types*Time seriesNetworksElectric gridGasUrbanGeo referenced grid 21903 segments 7174/1149 power stations 20481 subsGeo referenced pipelinesUrban streets mapsUrban transports Metro lines Railways9 Street classesElectrical grid disruptionsElectricity markets 25560 pipes 308 storage facilities 243 compressorsPlatts October 2007 datasets
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GIS gas transmission data pre-processElimination of minor grids (network reduction)*Network correctionsOriginal pipes dataset: 18981 linesReduced pipes dataset: 2702 lines Local utilities maps comparison Network visualization for connectivity errors detection
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*Topological discrepancies
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*GIS vs Map definitionSwiss Laufenburg substation UCTEGISSatelliteLaufenburg substationGeographical information system
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Generation of adjacency matrices*1. GIS data extraction2. Network grid compilation (IDfrom, IDto, value)4. GIS import of weighted values3. Matlab and Pajek data import and processing
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*Interconnected NetworksGIS gas and electricity networks
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Urban Networks*MilanTurin21553 nodes30119 edges18147 nodes26221 edges
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Available DatasestsWP 2 datasets https://manmade.jrc.it European electrical grid networkEuropean gas pipelines networkElectricity NordPool Spot pricesTurin urban streets networkMilan urban streets network
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Future stepsHigh computational capacity (maximum matrix size)Analysis of interconnected networks (gas and electricity)Urban Streets networks graph networks analysis and comparison (Turin and Milan)*
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