FLiER: Practical Topology Update Detection Using Sparse PMUs

TL;DR

FLiER is a practical method for detecting topology changes in power networks using sparse PMU data, employing a fast approximate algorithm based on voltage fingerprints to identify events efficiently.

Contribution

Introduces FLiER, a novel fast algorithm leveraging voltage fingerprints and linearization for topology change detection with sparse PMUs.

Findings

Effective detection of topology changes in standard test networks.

Algorithm achieves near-brute-force accuracy with significantly reduced computation time.

Applicable to large-scale power networks with sparse measurement deployment.

Abstract

In this paper, we present a Fingerprint Linear Estimation Routine (FLiER) to identify topology changes in power networks using readings from sparsely-deployed phasor measurement units (PMUs). When a power line, load, or generator trips in a network, or when a substation is reconfigured, the event leaves a unique "voltage fingerprint" of bus voltage changes that we can identify using only the portion of the network directly observed by the PMUs. The naive brute-force approach to identify a failed line from such voltage fingerprints, though simple and accurate, is slow. We derive an approximate algorithm based on a local linearization and a novel filtering approach that is faster and only slightly less accurate. We present experimental results using the IEEE 57-bus, IEEE 118-bus, and Polish 1999-2000 winter peak networks.