Abstract
The growing integration of intermittent renewable energy sources (RESs) into microgrids poses a serious challenge to the stability of grid inertia. This article focuses on these challenges and introduces an adaptive interval type-2 fractional fuzzy (IT2FF) based virtual inertia control (VIC) for renewable energy integrated hybrid multi-area microgrid. In addition, the Quasi-Oppositional Geometric Mean Optimizer (QOGMO) optimization is devised to adaptively update the controller's coefficients. Comparisons with alternative optimization methods are used to gauge the algorithm's efficacy and the stability of the grid. The findings demonstrate that the suggested algorithm outperforms current methods in significantly enhancing frequency stability under a variety of conditions, such as uncertainties, physical limitations, and a prevalence of green power. The strategy not only integrates inertia into the system but also adjusts it dynamically in response to frequency fluctuations. The study further explores the inertia boundaries and evaluates the stability of the test microgrid with the employed adaptive control. Further, the performance of the designed approach is contrasted with the existing control scheme, and the sensitivity analysis validates the resilience of the developed adaptive controller. Finally, an experimental analysis is performed using the OPAL-RT 4510 platform to demonstrate the effectiveness of the proposed strategy.
Published Version
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