Data-Driven Approach for Distribution Network Topology Detection

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.

5 Pages, Submitted to IEEE PES GM 2015, Denver, CO

References in corpus (3)

• Distributed reactive power feedback control for voltage regulation and loss minimization
• Load flow analysis of radial distribution network using linear data structure
• Chapter 34 - Every Moment Counts: Synchrophasors for Distribution Networks with Variable Resources

Cited by in corpus (7)

• On Identification of Distribution Grids
• Event Detection and Localization in Distribution Grids with Phasor Measurement Units
• Real-Time Topology Detection and State Estimation in Distribution Systems Using Micro-PMU and Smart Meter Data
• Micro-Synchrophasors for Power Distribution Monitoring, a Technology Review
• Topology Estimation in Bulk Power Grids: Guarantees on Exact Recovery
• Low-Voltage Distribution Network Impedances Identification Based on Smart Meter Data
• Learning Topology of Distribution Grids using only Terminal Node Measurements