The high penetration of inverter-based resources in islanded microgrids significantly reduces system inertia and damping, threatening frequency stability during load and generation mismatches. To address these challenges, this article presents a robust frequency control framework assisted by reduced-order modeling. First, the complex higher-order microgrid dynamics are approximated into a computationally efficient First-Order Plus Time-Delay (FOPTD) model. This reduced model is then utilized to synthesize robust controllers using five distinct deterministic rule-based tuning strategies, avoiding the computational burden of iterative optimization. The performance of the proposed approach is validated through real-time Hardware-in-the-Loop (HIL) simulations on an OPAL-RT platform, incorporating realistic scenarios such as stochastic load changes and renewable energy fluctuations. Furthermore, extensive sensitivity analysis demonstrates the controllers' robustness against parameter uncertainties, specifically under varying system inertia and damping conditions.
Singh, S.P., Singh, V.P., Benedetto, F., Guerrero, J.M. (2026). FOPTD Based Reduced Order Modeling Assisted Real Time Robust Frequency Control of Islanded Microgrid with Inverter-Based Resources. IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 1-11 [10.1109/TIA.2026.3694055].
FOPTD Based Reduced Order Modeling Assisted Real Time Robust Frequency Control of Islanded Microgrid with Inverter-Based Resources
Benedetto F.;
2026-01-01
Abstract
The high penetration of inverter-based resources in islanded microgrids significantly reduces system inertia and damping, threatening frequency stability during load and generation mismatches. To address these challenges, this article presents a robust frequency control framework assisted by reduced-order modeling. First, the complex higher-order microgrid dynamics are approximated into a computationally efficient First-Order Plus Time-Delay (FOPTD) model. This reduced model is then utilized to synthesize robust controllers using five distinct deterministic rule-based tuning strategies, avoiding the computational burden of iterative optimization. The performance of the proposed approach is validated through real-time Hardware-in-the-Loop (HIL) simulations on an OPAL-RT platform, incorporating realistic scenarios such as stochastic load changes and renewable energy fluctuations. Furthermore, extensive sensitivity analysis demonstrates the controllers' robustness against parameter uncertainties, specifically under varying system inertia and damping conditions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


