Data-Driven Approach for Distribution Network Topology Detection

TL;DR

This paper introduces a data-driven method utilizing real-time voltage measurements from phasor measurement units to detect topology changes in distribution networks, validated on the IEEE 33-bus model.

Contribution

It presents a novel algorithm that compares real-time voltage data with topology signatures to identify network topology transitions.

Findings

Effective detection of topology changes demonstrated on IEEE 33-bus system.

High accuracy in identifying switching actions and topology transitions.

Real-time analysis capability for distribution network monitoring.

Abstract

This paper proposes a data-driven approach to detect the switching actions and topology transitions in distribution networks. It is based on the real time analysis of time-series voltages measurements. The analysis approach draws on data from high-precision phasor measurement units ($\mu$PMUs or synchrophasors) for distribution networks. The key fact is that time-series measurement data taken from the distribution network has specific patterns representing state transitions such as topology changes. The proposed algorithm is based on comparison of actual voltage measurements with a library of signatures derived from the possible topologies simulation. The IEEE 33-bus model is used for the algorithm validation.