Intelligent and resilient techniques for dynamic behavior optimization in renewable energy systems

This study proposes an Improved Modified Invasive Weed Optimization-based PID (IMIWO-PID) controller for Hybrid Renewable Energy Systems (HRES). The novelty of the work lies in the integration of adaptive seed dispersal and Lévy flight strategies into the invasive weed optimization process, ensuring faster convergence, enhanced global search capability, and improved robustness against nonlinearities and uncertainties. Unlike most existing controllers, the proposed method is validated not only through simulation but also via Hardware-in-the-Loop (HIL) experiments, confirming its practical feasibility. A comparative analysis against Fractional-Order Proportional-Integral-Derivative (FO-PID), Fractional-Order Proportional-Derivative–Proportional-Integral (FO-(PD-PI)), Grey Wolf Optimization-based PID (GWO-PID), and Fractional-Order Fuzzy PID (FO-F-PID) demonstrates that the IMIWO-PID achieves significantly reduced overshoot, undershoot, and settling time while maintaining scalability for larger microgrid systems. The results indicate that the IMIWO-PID controller achieves undershoot values of 0.005289, 0.003, and 0.003119; overshoot values of 0.002023, 0.000702, and 0.00132; settling times of 2.09 s, 3.69 s, and 2.2 s; and performance indices of 2.537, 0.302, and 2.096 across varying test conditions. Sensitivity analysis further substantiates its robustness, with a performance index of 2.97. The novelty lies in the adaptive weed dispersal and Lévy flight integration, which enables faster convergence and enhanced resilience to uncertainties. Both simulation and Hardware-in-the-Loop (HIL) results demonstrate superior performance, with undershoot as low as 0.003 p.u., overshoot below 0.0007 p.u., and a settling time of 2.09 as compared to other controllers. The findings confirm that the IMIWO-PID minimizes transient deviations and ensures stable frequency regulation in complex HRES environments.