Abstract

In this paper it is proposed a novel high impedance fault detection and location scheme for power distribution feeders with distributed generation. The proposed scheme is capable to obtain precise fault location estimations for both linear low impedance and non-linear high impedance faults. This last class of faults represents an important subject for the power distribution utilities because they can be difficult to detect and locate by the protection devices commonly used in todays electric distribution systems. The proposed scheme uses real time data which are processed in a way that the fault detection and location can be estimated by a set of characteristics extracted from the voltage and current signals measured at the substation. This characteristic set is classified by an artificial neural network based scheme whose output results in a fault detection and location. The scheme is based on the calculation of the symmetrical components of the current signal harmonies at the relay point. Other traditional fault detection and location methodologies were also implemented, making possible to obtain comparative results. The scheme was applied in two simulated feeders. The results of this work shows, that the proposed methodology is worthy of continued research objecting real time applications.

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