Inertia Estimation in High-RES Power Systems Using Small-Signal Power Injection

This paper proposes a continuous inertia estimation framework for transmission-level power systems with high renewable energy penetration, using a battery energy storage system (BESS) as a controllable small-signal power injection source. The proposed framework integrates BESS-based active power injection, a two-stage signal-smoothing scheme, and a rate-of-change-of-frequency (RoCoF)-based estimation mechanism to enable continuous inertia estimation without relying on major disturbance events. With noise-robust processing and moving-window analysis, the framework can reliably track inertia variations under noisy measurement conditions and diverse operating scenarios. The framework is validated on the IEEE 39-bus system under renewable energy source (RES) penetration levels of 0%, 10%, 20%, and 30%. The estimation error remains within ±3.5% across all scenarios, ranging from 1.26% at 0% RES penetration to 3.43% at 30% penetration. In addition, the estimated inertia closely follows the theoretical decrease from 3.20 s to 2.22 s as RES penetration increases. These results demonstrate the accuracy and robustness of the proposed framework for continuous inertia monitoring in low-inertia power systems with high-RES penetration.

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Publication Details

Journal
Applied Sciences
Published
2026-04-24
DOI
https://doi.org/10.3390/app16094200
Primary Topic
Microgrid Control and Optimization
Type
article
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article

Inertia Estimation in High-RES Power Systems Using Small-Signal Power Injection

Yu-Min Hsin, Cheng‐Chien Kuo, Chia-Ming Chang
Applied Sciences
Microgrid Control and Optimization
article

Inertia Estimation in High-RES Power Systems Using Small-Signal Power Injection

Yu-Min Hsin, Cheng‐Chien Kuo, Chia-Ming Chang
article en

Abstract

This paper proposes a continuous inertia estimation framework for transmission-level power systems with high renewable energy penetration, using a battery energy storage system (BESS) as a controllable small-signal power injection source. The proposed framework integrates BESS-based active power injection, a two-stage signal-smoothing scheme, and a rate-of-change-of-frequency (RoCoF)-based estimation mechanism to enable continuous inertia estimation without relying on major disturbance events. With noise-robust processing and moving-window analysis, the framework can reliably track inertia variations under noisy measurement conditions and diverse operating scenarios. The framework is validated on the IEEE 39-bus system under renewable energy source (RES) penetration levels of 0%, 10%, 20%, and 30%. The estimation error remains within ±3.5% across all scenarios, ranging from 1.26% at 0% RES penetration to 3.43% at 30% penetration. In addition, the estimated inertia closely follows the theoretical decrease from 3.20 s to 2.22 s as RES penetration increases. These results demonstrate the accuracy and robustness of the proposed framework for continuous inertia monitoring in low-inertia power systems with high-RES penetration.

Applied SciencesVol. 16(9)
National Taiwan University of Science and Technology (TW)
Affordable and clean energy
Openalex Percentile: Top 8%
Microgrid Control and Optimization
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Inertia Estimation in High-RES Power Systems Using Small-Signal Power Injection — Yu-Min Hsin, Cheng‐Chien Kuo, et al. · Applied Sciences (2026) | TGRS Research Map | TGRS