Healthy and faulty mode detection in power distribution networks based on park transformation

Abstract Distribution Network (DN) face sundry transient conditions, resulting in incorrect detection of fault and mal-operation based on load type, capacity, and number of transformers in the operation mode. In this paper, a novel method is proposed to provide separability while increasing fault detection capability from other transient conditions in the DN, all in all by using the recorded currents at the beginning of feeder. Using current components of Park transformation, the method proposes a novel pattern, based on the graph of component d compared to component q of the current recorded at the beginning of the feeder, for analyzing transience in normal and faulty operation modes of the network. Fault curves and other transient trends of the DN, such as inrush current, inherit different characteristics that can be detected through classification. In this method, healthy and faulty operating modes are well distinguished in less than 2 ms. A sample of DN together with a real distribution feeder of Iran's Electricity Distribution Company is used to evaluate the proposed method. Simulation results verify the validity and accuracy of the proposed method.

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