# A Periodogram-Based Method to Identify Forced and Natural Oscillations Using PMUs

## TL;DR

This paper introduces a novel periodogram-based technique to differentiate between forced and natural oscillations in power systems using PMU data, enhancing the ability to identify oscillation mechanisms accurately.

## Contribution

The paper presents a new spectral analysis method that effectively distinguishes oscillation types in power systems, even with close frequency proximity.

## Key findings

- Accurately distinguishes oscillation mechanisms in power systems.
- Effective even when forced and natural oscillation frequencies are close.
- Provides a quantitative signature extraction from spectral data.

## Abstract

Sustained oscillations in power systems are dangerous. There are various mechanisms, for instance, limit cycle and forced oscillation, that may lead to sustained oscillations, which nevertheless are hard to differentiate. In this paper, a novel periodogram-based method to distinguish different oscillation mechanism is proposed, which can quantitatively extract essential signatures of different mechanisms from power spectral density. Numerical study shows that the proposed method can accurately distinguish different oscillation mechanisms even when the forced oscillation frequency is close to the natural frequency.