DIAGNOSING VULNERABILITY, EMERGENT PHENOMENA, and VOLATILITY in MANMADE NETWORKS WP2 Data Collation MANMADE COLB, Budapest of January 2008 F. Bono, E. Gutierrez
Data flow architecture 2
Attributes of Data Types 3 Time series Networks Electric grid Gas Urban Geo referenced grid segments 7174/1149 power stations subs Geo referenced pipelines Urban streets maps Urban transports Metro lines Railways 9 Street classes Electrical grid disruptions Electricity markets pipes 308 storage facilities 243 compressors Platts October 2007 datasets
GIS gas transmission data pre-process Elimination of minor grids (network reduction) 4 Network corrections Original pipes dataset: lines Reduced pipes dataset: 2702 lines Local utilities’ maps comparison Network visualization for connectivity errors detection
5 Tealing Kinfore Kincardine Topological discrepancies UCTE map GIS Platts dataset Tealing Kinfore Kincardine
6 GIS vs Map definition Swiss Laufenburg substation UCTE GIS Satellite Laufenburg substation Geographical information system
Generation of adjacency matrices 7 1. GIS data extraction 2. Network grid compilation (IDfrom, IDto, value) 4. GIS import of weighted values 3. Matlab and Pajek data import and processing
8 Interconnected Networks GIS gas and electricity networks
Urban Networks 9 Milan Turin nodes edges nodes edges nodes edges nodes edges
Available Datasests WP 2 datasets European electrical grid network European gas pipelines network Electricity NordPool Spot prices Turin urban streets network Milan urban streets network 10
Future steps High computational capacity (maximum matrix size) Analysis of interconnected networks (gas and electricity) Urban Streets networks graph networks analysis and comparison (Turin and Milan) 11