LQI-based control of grid-forming converters with a variable operating frequency droop mechanism: DMAT-based assessment

This paper proposes an enhanced droop-based grid-forming (GFM) converter control framework incorporating a variable operating frequency (VOF) mechanism to prevent active power limit violations during large frequency excursions. In addition, a linear quadratic integral (LQI)-based inner voltage controller is implemented and systematically compared with a classical cascaded PI structure within the same GFM configuration. The proposed approach is evaluated using selected model acceptance tests derived from the Australian Energy Market Operator (AEMO) Dynamic Model Acceptance Testing (DMAT) guidelines under grid conditions characterized by short circuit ratio (SCR) = 10 and X/R = 14 at the Point of Connection (POC). The proposed VOF mechanism maintained the inverter’s active power output within a predefined range of 0.5 pu to 1.15 pu during extreme frequency deviations. Furthermore, the FRT algorithm, designed separately for both PI and LQI-based models, kept the current below 1.2 pu. Across voltage, frequency, fault ride-through, and phase-angle disturbance tests, the LQI-based controller exhibits improved transient damping, reduced oscillatory behavior, and faster settling compared to the PI-based implementation, while maintaining comparable steady-state performance. The proposed framework is further validated on the IEEE 9-bus system under multi-machine fault conditions. The results provide a DMAT-based and quantitatively validated framework for enhancing droop-based GFM converter robustness under grid-code-relevant large disturbances in compliance with IEEE Std 2800-2022 requirements.

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Publication Details

Journal
Electric Power Systems Research
Published
2026-06-24
DOI
https://doi.org/10.1016/j.epsr.2026.113488
Primary Topic
Microgrid Control and Optimization
Type
article
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article

LQI-based control of grid-forming converters with a variable operating frequency droop mechanism: DMAT-based assessment

Sezai Taşkın, Çoşku Kasnakoğlu, Macit Tozak, İbrahim Şengör et al.
Electric Power Systems Research
Microgrid Control and Optimization
article

LQI-based control of grid-forming converters with a variable operating frequency droop mechanism: DMAT-based assessment

Sezai Taşkın, Çoşku Kasnakoğlu, Macit Tozak, İbrahim Şengör, Alper Cakiroglu
article en

Abstract

This paper proposes an enhanced droop-based grid-forming (GFM) converter control framework incorporating a variable operating frequency (VOF) mechanism to prevent active power limit violations during large frequency excursions. In addition, a linear quadratic integral (LQI)-based inner voltage controller is implemented and systematically compared with a classical cascaded PI structure within the same GFM configuration. The proposed approach is evaluated using selected model acceptance tests derived from the Australian Energy Market Operator (AEMO) Dynamic Model Acceptance Testing (DMAT) guidelines under grid conditions characterized by short circuit ratio (SCR) = 10 and X/R = 14 at the Point of Connection (POC). The proposed VOF mechanism maintained the inverter’s active power output within a predefined range of 0.5 pu to 1.15 pu during extreme frequency deviations. Furthermore, the FRT algorithm, designed separately for both PI and LQI-based models, kept the current below 1.2 pu. Across voltage, frequency, fault ride-through, and phase-angle disturbance tests, the LQI-based controller exhibits improved transient damping, reduced oscillatory behavior, and faster settling compared to the PI-based implementation, while maintaining comparable steady-state performance. The proposed framework is further validated on the IEEE 9-bus system under multi-machine fault conditions. The results provide a DMAT-based and quantitatively validated framework for enhancing droop-based GFM converter robustness under grid-code-relevant large disturbances in compliance with IEEE Std 2800-2022 requirements.

Electric Power Systems ResearchVol. 261
TOBB University of Economics and Technology (TR), Manisa Celal Bayar University (TR), Şifa University (TR), Munster Technological University (IE)
Affordable and clean energy
Openalex Percentile: Top 8%
Microgrid Control and Optimization
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