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Sustained and incipient fault location for utility distribution system

Automated fault location systems use power quality monitoring and circuit data to provide with a distance or impedance estimate to the fault. This can be used to avoid manual patrolling of the entire feeder in case of a main feeder lockout. It can also be used for circuits with repeated momentary interruptions to pinpoint the section of the circuit causing such problems.
Self clearing sub cycle faults have been identified as the precursors of a number of sustained faults (requiring the operation of protective device) in utility distribution networks. The frequency of such incipient faults increases considerably as they are about to evolve into a full blown fault.
This report proposes a modified and improved fault location algorithm that can be used to accurately identify sustained as well as temporary faults. The algorithm is based in the time domain and takes into account the arc voltage during a fault event. The proposed algorithm is developed, validated and applied to known distribution field data. Time domain simulation models are also used for validation purposes. The developed algorithm was observed to be very accurate when compared to other impedance based fault location algorithms proposed in the literature. Finally, sub cycle event identification and fault pre-location is proposed that can be very useful for electric utility operations. Highly accurate results were observed during this application study. For instance, a current waveform containing three incipient and one full fault event is shown in the figure given below. The estimated reactance to an incipient fault location is approximately 1.1 Ω. The fault location results obtained from the first three sub-cycle faults can be used to avert the final sustained fault event. / text

Identiferoai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2009-12-500
Date20 September 2010
CreatorsChopra, Shivaz
ContributorsSantoso, Surya
Source SetsUniversity of Texas
LanguageEnglish
Detected LanguageEnglish
Typethesis
Formatapplication/pdf

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