Graph-based Faulted Line Identification Using Micro-PMU Data in Distribution Systems
Abstract
Motivated by increasing penetration of distributed generators (DGs) and fast development of micro-phasor measurement units ({\mu}PMUs), this paper proposes a novel graph-based faulted line identification algorithm using a limited number of {\mu}PMUs in distribution networks. The core of the proposed method is to apply advanced distribution system state estimation (DSSE) techniques integrating {\mu}PMU data to the fault location. We propose a distributed DSSE algorithm to efficiently restrict the searching region for the fault source in the feeder between two adjacent {\mu}PMUs. Based on the graph model of the feeder in the reduced searching region, we further perform the DSSE in a hierarchical structure and identify the location of the fault source. Also, the proposed approach captures the impact of DGs on distribution system operation and remains robust against high-level noises in measurements. Numerical simulations verify the accuracy and efficiency of the proposed method under various fault scenarios covering multiple fault types and fault impedances.
Cite
@article{arxiv.2002.10966,
title = {Graph-based Faulted Line Identification Using Micro-PMU Data in Distribution Systems},
author = {Ying Zhang and Jianhui Wang and Mohammad Khodayar},
journal= {arXiv preprint arXiv:2002.10966},
year = {2020}
}