Introduction
As a vital lifeline of the modern society for maintaining adequate and reliable flows of energy, power distribution systems deliver the electricity from high voltage transmission circuits to customers. Any interruption in their service may cause economical loss, damage equipments, and even endanger people lives. When a power outage (i.e., the loss of the electricity supply to an area) occurs, it is of great importance to diagnose the fault and restore the system in a timely manner in order to maintain the system availability and reliability. However, the restoration process may take from tens of minutes to hours. Most utilities for safety concerns do not restore the system until the outage cause has been found: linemen may need to inspect the distribution lines section by section in an attempt to find evidences (e.g., burn marks on the pole for possible lightning caused faults, dead animal bodies for possible animal activity related faults) and to ensure safety prior to re-energizing the system (e.g., no down distribution lines). Sometimes specific crew need to be further dispatched for advanced tasks such as the removal of fallen trees. Effective identification of either the cause or the location of the outage can provide valuable information to expedite the restoration procedure.
This work is supported by National Science Foundation Grant ECS-0245383.
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Xu, L., Chow, MY. (2008). Power Distribution System Fault Diagnosis Using Hybrid Algorithm of Fuzzy Classification and Artificial Immune Systems. In: Prasad, B. (eds) Soft Computing Applications in Industry. Studies in Fuzziness and Soft Computing, vol 226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77465-5_18
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