Optimal Interval based tuning of 3DOF-PID controllers for power system stabilizers and dynamic performance in multi machine power systems

Abstract

The removal of inadequately damped oscillations is necessary to guarantee the dependability and security of electrical power systems. This is especially crucial in modern power grids, where increasing interconnections between systems amplify the importance of stability. This manuscript proposes a Snow Ablation Optimizer (SAO) for optimal interval-based tuning of three degrees of freedom proportional-integral-derivative tilted-integral (3DOF-PID-TI) Controller for power system stabilizers (PSS) and dynamic performance in multi-machine power systems. The main objective is to optimize the performance of the PSS to enhance stability and effectively damp oscillations in power systems. The 3DOF-PID-TI controller parameter is adjusted using the SOA method. By then, the proposed approach has been incorporated into the MATLAB working platform, and the execution is calculated using the current system. The proposed technique displays better results in all existing methods such as the Wolf Optimizer algorithm (GWO), the Mayfly Optimization Algorithm (MOA), Improved Whale Optimization Algorithm (IWOA). The proposed method achieves 97%, surpassing the existing techniques with GWO at 84%, MOA at 76%, and IWOA at 64%. Additionally, the proposed SAO method demonstrates a settling time of 1.312 seconds, while the existing methods have longer settling times: GWO at 1.811 seconds, MOA at 2.969 seconds, and IWOA at 2.572 seconds. This enhancement highlights the better performance and optimization capability of the proposed method, emphasizing its effectiveness in optimizing PSS in multi-machine power systems contrasted to conventional optimization approaches.