There are many calamitous events such as earthquakes, hurricanes, tsunamis etc. that occur suddenly and cause great loss of life, damage, or hardship. Hurricanes cause significant damage to power distribution systems, resulting in prolonged customer outages and excessive delays in the reconstruction efforts. Accordingly, predicting the effects of power outages on the performance of power distribution systems is of major importance to government agencies, utilities, and customers. Unfortunately, the current tools to predict the performance of power distribution systems during catastrophic events are limited in both the performance measures considered, as well as in their ability to model real systems.
The main goal of this research is to develop a methodology for simulating hurricanes of different intensity on power distribution systems of small and medium size cities. Our study includes a detailed comparison between the engineering-based and connectivity-based models of power distribution systems, as well as the impact of power re-routing algorithms on the system reliability. Our approach is based on fragility curves that capture the ability of the system to withstand a range of wind speeds. In addition, we develop a multiscale approach that facilitates efficient computation of fragility curves for large cities. With this approach, hurricanes are simulated over small zones of a city and fragility curves are obtained. These are used to estimate the damage for identical zones throughout the city. To validate our techniques, two testbeds, Micropolis and Mesopolis, were used. Micropolis is synthetic model for a small city and Mesopolis for a big city. Obtained results have validated our approach and have shown that they can be used to effectively predict hurricane damage.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2011-08-9810 |
| Date | 2011 August 1900 |
| Creators | Chanda, Suraj |
| Contributors | Singh, Chanan, Sprintson, Alex |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | thesis, text |
| Format | application/pdf |
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