Inertia Estimation of Regional Power Systems Using Band-Pass Filtering of PMU Ambient Data

This paper proposes a regional inertia estimation method in power systems using ambient data measured by phasor measurement units (PMUs). The proposed method employs band-pass filtering to suppress the low-frequency influence of mechanical power and to attenuate high-frequency noise and discrepancies between rotor speed and electrical frequency. By utilizing a simple first-order AutoRegressive Moving Average with eXogenous input (ARMAX) model, this process allows the inertia constant to be directly identified. This method requires no prior model order selection, rotor speed estimation, or computation of the rate of change of frequency (RoCoF). The proposed method was validated through simulation on three benchmark systems: the Kundur two-area system, the IEEE Australian simplified 14-generator system, and the IEEE 39-bus system. The method achieved area-level inertia estimates within approximately ±5% error across all test cases, exhibiting consistent performance despite variations in disturbance models and system configurations. The estimation also maintained stable performance with short data windows of a few minutes, demonstrating its suitability for near real-time monitoring applications.

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Publication Details

Journal
Energies
Published
2026-01-15
DOI
https://doi.org/10.3390/en19020424
Primary Topic
Power System Optimization and Stability
Type
article
Field-Weighted Citation Impact
0.00

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article

Inertia Estimation of Regional Power Systems Using Band-Pass Filtering of PMU Ambient Data

Kyeong-Yeong Lee, Sung‐Guk Yoon, Jin Kwon Hwang
Energies
Power System Optimization and Stability
article

Inertia Estimation of Regional Power Systems Using Band-Pass Filtering of PMU Ambient Data

Kyeong-Yeong Lee, Sung‐Guk Yoon, Jin Kwon Hwang
article en

Abstract

This paper proposes a regional inertia estimation method in power systems using ambient data measured by phasor measurement units (PMUs). The proposed method employs band-pass filtering to suppress the low-frequency influence of mechanical power and to attenuate high-frequency noise and discrepancies between rotor speed and electrical frequency. By utilizing a simple first-order AutoRegressive Moving Average with eXogenous input (ARMAX) model, this process allows the inertia constant to be directly identified. This method requires no prior model order selection, rotor speed estimation, or computation of the rate of change of frequency (RoCoF). The proposed method was validated through simulation on three benchmark systems: the Kundur two-area system, the IEEE Australian simplified 14-generator system, and the IEEE 39-bus system. The method achieved area-level inertia estimates within approximately ±5% error across all test cases, exhibiting consistent performance despite variations in disturbance models and system configurations. The estimation also maintained stable performance with short data windows of a few minutes, demonstrating its suitability for near real-time monitoring applications.

EnergiesVol. 19(2)
Soongsil University (KR), Woosuk University (KR)
National Research Foundation, National Research Foundation of Korea, Ministry of Science and ICT, South Korea, Korea Institute of Energy Technology Evaluation and Planning
Openalex Percentile: Top 87%
Power System Optimization and Stability
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Inertia Estimation of Regional Power Systems Using Band-Pass Filtering of PMU Ambient Data — Kyeong-Yeong Lee, Sung‐Guk Yoon, et al. · Energies (2026) | TGRS Research Map | TGRS