Transmission Lines Fault Location: A Mathematical Morphology-Based Approach

Cavalcante, Paulo A. H.; Trindade, Fernanda C. L.; Almeida, Madson C. de

doi:10.1007/s40313-013-0028-z

Cited by 4 publications

(1 citation statement)

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“…With the mean seasonality information for each distance value it is possible to calculate an adjustment curve relating the two terms. This can be done by using the method of least squares (MLS) [12]. The generation of a polynomial relating seasonality to distance allows the estimation for several fault situations only with the information of the value of seasonality.…”

Section: The Proposed Methodsmentioning

confidence: 99%

Fault Location in Power Transmission Lines using Autocorrelation Function

Souza¹,

Christo²,

Almeida³

et al. 2018

IJAERS

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An electrical power system is subject to constant adversities due to its complexity, sensitivity and physical dimensions. Special emphasis is given to transmission lines (TL) that are the most vulnerable elements of an electrical system. Although most of the occurrences of distortions in the voltage signals from atmospheric discharges and overload are not detrimental to the energy supply, it is important to have control of these currents, since this allows the classification of the fault type and its geometric location on the transmission line. This study aims to compare different fault situations in a transmission line and to verify changes in time series models (TS). This study was carried out through computational tests performed with MatLAB®and RStudio® software. A total of 272faults were simulated in different situations. The obtained results were compared with the Traveling Wave Theory (TWT), another quite widespread fault localization technique. The above study revealed the applicability of time series in oscillographic data of fault situations in transmission lines with errors lower than 1.25%.

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Section: The Proposed Methodsmentioning

confidence: 99%