الفهرس 
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Abstract
Electric power systems have rapidly grown for the past fifty
years. As a result, the number of cables in operation and their total
length had largely increased. Underground cables have been widely
implemented due to reliability and environmental concerns. To
improve the reliability of a distribution system, accurate
identification of a faulted segment is required in order to reduce the
interruption time during fault. Speedy and precise fault location
plays an important role in accelerating system restoration, reducing
outage time, reducing great financial loss and significantly
improving system reliability.
Therefore, this study presents a fault identification,
classification and fault location estimation method based on
Discrete Wavelet Transform and Adaptive Network Fuzzy
Inference System (ANFIS) for medium voltage cable in distribution
system.
Different faults and locations are simulated by ATP/EMTP,
and then certain selected features of the wavelet transformed signals
are used as an input for a training process on the ANFIS. Then an
accurate fault classifier and locator algorithm was designed, trained
and tested using current samples only. The results obtained from
ANFIS output were compared with the real output. from the
results, it was found that the percentage error between ANFIS
output and real output is less than three percent. Hence, it can be
concluded that the proposed technique is able to offer high accuracy
in both of the fault classification and