Automated Anomaly Detection in Distribution Grids Using $\mu$PMU Measurements

TL;DR

This paper proposes an automated method for detecting anomalies in distribution grids using micro-PMU measurements, enhancing grid visibility and security for distribution system operators.

Contribution

It introduces a novel anomaly detection approach leveraging micro-PMU data, supporting real-time monitoring and addressing security concerns in distribution grids.

Findings

Effective detection demonstrated on real data

Method performs well with simulated data

Enhances situational awareness for DSOs

Abstract

The impact of Phasor Measurement Units (PMUs) for providing situational awareness to transmission system operators has been widely documented. Micro-PMUs ($\mu$PMUs) are an emerging sensing technology that can provide similar benefits to Distribution System Operators (DSOs), enabling a level of visibility into the distribution grid that was previously unattainable. In order to support the deployment of these high resolution sensors, the automation of data analysis and prioritizing communication to the DSO becomes crucial. In this paper, we explore the use of $\mu$PMUs to detect anomalies on the distribution grid. Our methodology is motivated by growing concern about failures and attacks to distribution automation equipment. The effectiveness of our approach is demonstrated through both real and simulated data.