Outage Detection for Distribution Networks Using Limited Number of Power Flow Measurements

Abstract

Accurate topology estimation is crucial for effectively operating modern distribution networks. Line outages in a distribution network change the network topology by disconnecting some parts of the network from the main grid. In this paper, an outage detection (or topology estimation) algorithm for radial distribution networks is presented. The algorithm utilizes noisy power flow measurements collected from a subset of lines in the network, and statistical information characterizing errors in forecasting load demands. Additionally, a sensor placement scheme is presented. The sensor placement provides critical sensing for the outage detection algorithm so that any number of possible outages in the network can be detected. The performance of the proposed outage detection algorithm using the proposed sensor placement is demonstrated through several numerical results on the IEEE 123-node test feeder.

Learning Power Grid Outages With Higher-Order Topological Neural Networks

“…The smart meters in this class can also provide the voltage and current magnitudes at several points in the network. Others such as micro-PMUs and linewatch sensors provide the real and reactive power flows along the lines incident to the node at which these are placed [13]. Time series measurements from PMUs specifically designed for DNs are also being employed for analytics and diagnostics.…”