Abstract

Distribution networks are most prone to high impedance faults (HIFs). These types of faults occur whenever an energized conductor makes a contact with some surfaces that are poor conductors such as sand, concrete, branches of trees, etc. The consequential fault current has an absolute magnitude similar to that of load current therefore, the overcurrent relays usually fail to operate correctly during these faults. In the past few decades, several schemes have surfaced for detecting HIFs. The studies conducted in this article suggest an application of discrete wavelet transform to obtain discriminative features of faulty current signals and the development of a threshold-based scheme to discriminate between faulty and nonfaulty situations. The first-level approximate wavelet coefficients are extracted and used to calculate the standard deviation features using a recursive moving window. With the help of these features, faulted phase is also identified simultaneously apart from fault detection. The efficacy of the scheme is tested on a modified IEEE-13 bus test feeder system incorporated with distributed generators. The algorithm has been compared with the conventional HIF detection schemes and the results proved the efficiency and robustness of the proposed scheme to detect the fault under a variety of fault conditions. The main contributions of the proposed scheme are viz., it can correctly differentiate between HIF/LIF and switching events and works well on both grid-connected or islanding mode. Finally, validation with real field fault events captured by digital fault recorder confirms that the proposed framework can assist utility engineers in detecting the HIF/LIF and switching events securely.

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