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Energies 2017, 10(10), 1596;

Location of Faults in Power Transmission Lines Using the ARIMA Method

Computational Modeling in Science and Technology (MCCT), Fluminense Federal University (UFF), Volta Redonda 21941-916, Brazil
Technology Center, Federal University of Piauí (UFPI), Teresina 60455-760, Brazil
Author to whom correspondence should be addressed.
Received: 11 August 2017 / Revised: 23 September 2017 / Accepted: 6 October 2017 / Published: 13 October 2017
(This article belongs to the Special Issue Distributed Energy Resources Management)
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One of the major problems in transmission lines is the occurrence of failures that affect the quality of the electric power supplied, as the exact localization of the fault must be known for correction. In order to streamline the work of maintenance teams and standardize services, this paper proposes a method of locating faults in power transmission lines by analyzing the voltage oscillographic signals extracted at the line monitoring terminals. The developed method relates time series models obtained specifically for each failure pattern. The parameters of the autoregressive integrated moving average (ARIMA) model are estimated in order to adjust the voltage curves and calculate the distance from the initial fault localization to the terminals. Simulations of the failures are performed through the ATPDraw ® (5.5) software and the analyses were completed using the RStudio ® (1.0.143) software. The results obtained with respect to the failures, which did not involve earth return, were satisfactory when compared with widely used techniques in the literature, particularly when the fault distance became larger in relation to the beginning of the transmission line. View Full-Text
Keywords: transmission line; fault localization; time series; ARIMA; discrete wavelet transformer transmission line; fault localization; time series; ARIMA; discrete wavelet transformer

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Pinto Moreira de Souza, D.; da Silva Christo, E.; Rocha Almeida, A. Location of Faults in Power Transmission Lines Using the ARIMA Method. Energies 2017, 10, 1596.

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