Graph Analysis to Fully Automate Fault Location Identification in Power Distribution Systems

TL;DR

This paper introduces graph analysis techniques that automate fault location identification in power distribution systems, using basic data to automatically determine topology and fault locations without human intervention.

Contribution

It presents a novel, scalable graph analysis approach that automates fault detection and location in power systems without complex renumbering or manual steps.

Findings

Effective fault location identification demonstrated on IEEE 34-bus system

No need for complex node/branch renumbering or human intervention

Applicable to power systems of any size

Abstract

This paper proposes graph analysis methods to fully automate the fault location identification task in power distribution systems. The proposed methods take basic unordered data from power distribution systems as input, including branch parameters, load values, and the location of measuring devices. The proposed data preparation and analysis methods automatically identify the system's topology and extract essential information, such as faulted paths, structures, loading of laterals and sublaterals, and estimate the fault location accordingly. The proposed graph analysis methods do not require complex node and branch numbering processes or renumbering following changes in the system topology. The proposed methods eliminate the need for human intervention at any step of the fault location identification process. They are scalable and applicable to systems of any size. The performance of the proposed algorithm is demonstrated using the IEEE 34-bus distribution test system.