journal article·2026-04-24Open access

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

Chia-Ming Chang, Yu-Min Hsin, Cheng-Chien Kuo

Applied Sciences· Volume 16· Issue 9

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.
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Research context

OpenAlex topics: Microgrid Control and Optimization · Wind Turbine Control Systems · Power System Optimization and Stability

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan

Graduate Institute of Energy and Sustainability Technology, National Taiwan University of Science and Technology, Taipei 10607, Taiwan

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