DIAGNOSING VULNERABILITY, EMERGENT PHENOMENA, and VOLATILITY in MANMADE NETWORKS

WP2 Data CollationMANMADEMANMADECOLB, Budapest 21-22 of January 2008F. Bono, E. Gutierrez

Data flow architecture*

Database

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

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

*Topological discrepancies

*GIS vs Map definitionSwiss Laufenburg substation UCTEGISSatelliteLaufenburg substationGeographical information system

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

*Interconnected NetworksGIS gas and electricity networks

Urban Networks*MilanTurin21553 nodes30119 edges18147 nodes26221 edges

Available DatasestsWP 2 datasets https://manmade.jrc.it European electrical grid networkEuropean gas pipelines networkElectricity NordPool Spot pricesTurin urban streets networkMilan urban streets network

*

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)*

*