Bagchi, Arijit (2009-11). Modeling the Power Distribution Network of a Virtual City and Studying the Impact of Fire on the Electrical Infrastructure. Master's Thesis.
Thesis
The smooth and reliable operation of key infrastructure components like water distribution systems, electric power systems, and telecommunications is essential for a nation?s economic growth and overall security. Tragic events such as the Northridge earthquake and Hurricane Katrina have shown us how the occurrence of a disaster can cripple one or more such critical infrastructure components and cause widespread damage and destruction. Technological advancements made over the last few decades have resulted in these infrastructure components becoming highly complicated and inter-dependent on each other. The development of tools which can aid in understanding this complex interaction amongst the infrastructure components is thus of paramount importance for being able to manage critical resources and carry out post-emergency recovery missions. The research work conducted as a part of this thesis aims at studying the effects of fire (a calamitous event) on the electrical distribution network of a city. The study has been carried out on a test bed comprising of a virtual city named Micropolis which was modeled using a Geographic Information System (GIS) based software package. This report describes the designing of a separate electrical test bed using Simulink, based on the GIS layout of the power distribution network of Micropolis. It also proposes a method of quantifying the damage caused by fire to the electrical network by means of a parameter called the Load Loss Damage Index (LLDI). Finally, it presents an innovative graph theoretic approach for determining how to route power across faulted sections of the electrical network using a given set of Normally Open switches. The power is routed along a path of minimum impedance. The proposed methodologies are then tested by running numerous simulations on the Micropolis test bed, corresponding to different fire spread scenarios. The LLDI values generated from these simulation runs are then analyzed in order to determine the most damaging scenarios and to identify infrastructure components of the city which are most crucial in containing the damage caused by fire to the electrical network. The conclusions thereby drawn can give useful insights to emergency response personnel when they deal with real-life disasters.
