In many outage management systems, customer trouble calls have been used as the primary source of outages for distribution level outages. However the information from the trouble calls is not completely reliable as they lead to problems like okay-on-arrival reports, over escalation and extended outage times for the customers. But with the recent developments in communication and information technologies, utilities started to adopt Automated Meter Reading systems for their operational needs. In this thesis, an algorithm is developed and implemented that makes efficient use information available from the customers and powerline communication based AMR systems for outages. The work has taken advantage of the polling feature of powerline based AMR systems to identify the scope of the outage. The polling procedure uses the on demand read feature of the AMR systems that allows the utility to communicate directly with the customers. The meters in the neighborhood of the trouble calls are polled to identify the affected customers and the outages are located by back tracking to common point. In the first part of the algorithm, the distribution system is modeled as a tree and the meters are strategically polled based on the customers reporting the outages. The outage areas are identified and escalated to find the actual outage location. The crew can be directed to the outage scene to fix the cause of the outage. The algorithm discusses the rules to identify single outages, single customer outages and multiple outages. The algorithm was tested on different test systems representing distribution systems of various sizes. The algorithm is tested for different outage scenarios for all the test cases.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-4420 |
| Date | 08 May 2004 |
| Creators | Venganti, Thirupathi |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
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