https://isee.ui.ac.ir/ Computational Intelligence in Electrical Engineering en daily 1 Fri, 22 May 2026 00:00:00 +0330 Fri, 22 May 2026 00:00:00 +0330 https://isee.ui.ac.ir/article_30463.html The increasing penetration of non-synchronous renewable energy sources has significantly reduced system inertia, posing serious challenges to power system frequency stability. Battery Energy Storage Systems (BESS) have emerged as an effective solution for providing fast frequency support through virtual inertia and primary frequency control. This paper proposes a hybrid frequency control strategy for BESS that integrates virtual inertia control and virtual droop control to enhance both transient and steady-state frequency response. In addition, a novel Repeatable Optimization Algorithm (ROA) is developed to optimally tune the control parameters of the proposed BESS model and the associated PID controller. The effectiveness of the proposed approach is validated through detailed MATLAB/Simulink simulations on both single-area and four-area interconnected power systems under severe load disturbances. Comparative studies with several well-known optimization algorithms demonstrate that the proposed ROA achieves faster convergence, reduced frequency deviation, improved RoCoF, and shorter settling time. The results confirm that the proposed control and optimization framework provides a robust and efficient solution for frequency regulation in low-inertia power systems. https://isee.ui.ac.ir/article_30466.html Maintaining safe and reliable trajectories for multiple Unmanned Aerial Vehicles (UAVs) in environments with obsta-cles and external disturbances, such as wind, remains a significant challenge. This paper presents a novel trajectory replanning approach for a group of UAVs in the presence of wind disturbances. The proposed method is based on re-flecting the impact of any uncertainty caused by disturbances as an uncertainty in the dynamic response of the quad-rotor, through the application of the forward reachable sets (FRSs) theory on the motion equations. This results in a location ellipsoid error for each quadrotor. Combining this error ellipsoid with the quadrotor's physical dimensions via a Minkowski sum yields an expanded safety ellipsoid. To avoid inter-UAV collisions, a separating hyperplane is con-structed between pairs of safety ellipsoids at each replanning instant. Furthermore, the adaptation of the trajectory to instantaneous conditions is made possible through the application of a virtual force field at each point on the trajecto-ry. This force field accounts for both the intensity of wind disturbance and the proximity of the trajectory to surround-ing obstacles and other quadrotors (delimited by hyperplanes), allowing the trajectory to be reconfigured while preserv-ing some key optimal characteristics. Simulation results obtained in Matlab demonstrate the effectiveness of the proposed trajectory replanning framework and provide a comparative evaluation of its reduced computational cost.