Intelligence controlled frequency regulation and stability in renewable-powered islanded microgrid environments

One of the main drawbacks of an islanded microgrid is its low system inertia, which makes it highly sensitive to fluctuations in load demand and renewable generation. This results in poor dynamic response, unstable frequency deviations, and difficulties sustaining dependable operation in the absence of an efficient controller. To address this, a microgrid model with an islanded configuration is developed, consisting of multiple renewable sources. To enhance constancy, a cascaded fractional-order proportional integral–fractional-order proportional integral derivative controller with derivative filter is employed. The fractional-order structure improves flexibility and robustness, while the cascaded design enhances dynamic performance. The controller specifications are optimally adjusted using the Giant Armadillo Frilled Lizard Optimization algorithm. The model is tested in the MATLAB environment, considering various operating conditions such as renewable power fluctuations, varying load demands, and changing sampling periods. For fair validation, the suggested controller is related to the various existing controllers. The proposed controller method effectively limits frequency deviations to only ±2–3 p.u., with minimal control input (±0.2 p.u.) and the fastest settling time of about 2–3 s, making it the most efficient and robust solution for renewable-powered islanded microgrids.