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A novel selectivity technique to estimate the faulty feeder in MV networks was introduced in [1]. This technique depended on the directionality of discrete wavelet transform (DWT) detail coefficient of a residual current of each feeder with respect to the DWT detail coefficient of the residual voltage. The algorithm efficacy has been examined with high impedance arcing fault due to leaning trees....
Electrical faults due to leaning trees have been studied in [1]-[2] and it was found that the initial transients due to the associated arc reignitions are behavioral traits. These transients have been localized using the discrete wavelet transform (DWT). In this paper, these features are extracted from residual voltages using DWT. Therefore, the fault localization is carried out. The term for locating...
In this paper, the initial transients in the electrical network due to arc reignitions associated with high impedance faults caused by leaning trees are extracted from phase voltages and currents. The discrete wavelet transform (DWT) is used for the fault feature extraction corresponding to band frequency 12.5- 6.25 kHz and therefore localizing this fault occurrence. The detection security is enhanced...
In this paper, features of earth faults due to leaning trees are extracted from the network phase currents using the discrete wavelet transform (DWT). Due to the associated arc reignitions, the initial transients in the electrical network give behavioral traits. The detection security is also enhanced because the DWT is responded to a periodicity of the initial transients. The absolute sum of the...
In this paper, a high impedance arcing fault of the tree leaning type in medium voltage (MV) networks is modeled and experimentally verified. The fault is represented as two parts; an arc model and a high resistance. The arc is generated by the tree leaning towards the network conductor and the tree resistance limits the fault current. The arcing element is dynamically simulated using thermal equations...
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