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Real-Time Inertia Estimation and Adaptive-Model-Predictive-Control-Based Virtual Inertia Support for Frequency Control in Low-Inertia Systems

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Abstract

This study presents adaptive virtual inertia strategy supported by a model-predictive-control (MPC)-based real-time inertia estimation method. The proposed approach aims to mitigate frequency stability problems caused by low inertia in isolated power systems with high penetration of photovoltaics. The system inertia is estimated using frequency measurements obtained from phasor measurement unit. Based on the obtained real-time inertia information, the PI gains ( (Formula presented.) and (Formula presented.) ) in load frequency control unit and virtual inertia gain ( (Formula presented.) ) are updated simultaneously via MPC-based adaptive mechanism. In the first scenario, it was shown that under 10% PV penetration, the system inertia decreased from 5.00 s to 4.54 s, and the system became more sensitive to load changes. The proposed adaptive battery energy storage system support shows that a load change of 0.1 p.u. results in a response of 0.079 p.u. in 0.17 s. The adaptive BESS response raises frequency nadir from 49.6892 Hz to 49.9635 Hz, improving maximum frequency deviation by 88.25%. In the second scenario, it was observed that method maintained its stability even when the system inertia dropped to 3.33 s in 10–50% PV penetration range. This study presents integrated and innovative frequency control strategy for modern isolated power systems.

Original languageEnglish
Article number2161
JournalApplied Sciences (Switzerland)
Volume16
Issue number4
DOIs
Publication statusPublished - Feb 2026

Bibliographical note

Publisher Copyright:
© 2026 by the author.

Keywords

  • adaptive model predictive control
  • extended Kalman filter
  • frequency stability
  • isolated power systems
  • low-inertia
  • real-time inertia estimation
  • virtual inertia support

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