Impedance-Based Approach for Locating Short-Circuit Faults in Inverter-Based Active Distribution Networks.

This paper proposes an impedance-based approach for locating short-circuit faults in active distribution networks (DNs). This topic is a crucial task for operators, especially in grids with inverter-based distributed generators (IBDGs). Various methods have been proposed in this research area, including traveling waves, impedance-based methods, and artificial intelligence (AI) techniques. Among them, the impedance-based scheme offers a straightforward and efficient feature suitable for integration with AI-based techniques. This paper introduces an enhanced fault localization method based on impedance estimation, consisting of two main components: (i) fault distance determination and (ii) faulty section identification. This method accounts for the modeling of inverter-based resources under both symmetrical and asymmetrical faults, incorporating the impact and behavior of such sources. Unlike conventional impedance-based methods, our approach does not require network information such as structure, lines, load data, or voltage and current measurements along the feeder at multiple points. It can serve as a feature in AIbased techniques, significantly enhancing accuracy and reducing the complexity of such techniques. To validate the efficacy of the proposed approach, we conducted a series of time-domain case studies and provided mathematical proofs. The results demonstrate the effectiveness of our scheme in accurately locating faults with varying resistances at different positions in the presence of IBDGs. [ABSTRACT FROM AUTHOR]