Tracking disturbances in transmission networks

TL;DR

This paper investigates methods for detecting, localizing, and identifying unknown disturbances in transmission networks using strategic observation sets, demonstrating that certain conditions enable real-time identification through numerical experiments.

Contribution

It introduces conditions on observation sets that guarantee detection, localization, and identification of disturbances in transmission networks, including the concept of absorbent sets for real-time analysis.

Findings

Strategic observation sets suffice for disturbance detection.

Absorbent sets enable localization and identification.

Real-time detection is possible with dominantly absorbent sets.

Abstract

We study the nonlinear inverse source problem of detecting, localizing and identifying unknown accidental disturbances on forced and damped transmission networks. A first result is that strategic observation sets are enough to guarantee detection of disturbances. To localize and identify them, we additionally need the observation set to be absorbent. If this set is dominantly absorbent, then detection, localization and identification can be done in "quasi real-time". We illustrate these results with numerical experiments.