Dynamic Stabilizer Analysis and Optimization in Multi-Machine Power Systems: A Novel Approach Based on Adaptive Control and Artificial Intelligence

Power System Stabilizers (PSS) are integrated into generator excitation systems to enhance the damping of low-frequency oscillations during disturbances. In large-scale and multi-machine power systems, the presence of poorly damped oscillatory modes makes the optimal tuning of PSS parameters a complex and time-consuming task. Moreover, continuous variations in operating conditions and network load levels lead to changes in the system's dynamic characteristics and shifts in oscillation modes, thereby reducing the effectiveness of PSSs with fixed settings. Since most PSS designs are based on the single-machine infinite bus (SMIB) model and tuned for a specific operating point, any change in network parameters or operating conditions may jeopardize overall system stability. This study proposes a novel approach based on artificial intelligence and adaptive fuzzy control for the design and optimization of dynamic stabilizers in a two-area multi-machine power system. The main objective is to improve the damping of electromechanical oscillations and ensure system stability across a wide range of parameter variations and operating scenarios.

کلیدواژه ها:

Power System Stabilizer (PSS) ، Multi-Machine Power System ، Adaptive Fuzzy Control ، Oscillation Damping ، Artificial Intelligence