Radial Basis Function Network-Based Static Synchronous Series Compensator For Power System Security Enhancement

Abstract

Power system oscillation presents a substantial risk to the stability of power systems. The impact of oscillation damping significantly influences the safety of contemporary power systems. This research explores the enhancements in power security by improving transient stability and damping oscillation by using a Radial Basis Function Network (RBFN)-based Static Synchronous Series Compensator (SSSC). A comparison between two controllers, the conventional PI controller and the RBFN, reveals that the neural network based controller demonstrates superior dynamic performance over the typical proportional integral (PI) controller. RBFN controller is design to achieve, during disturbances promptly reduces power oscillations and enhances power flow control as compared to the PI controller. The proposed controller is designed with two signals, reference voltage and measured voltage at SSSC location. The training data developed with difference between reference voltage and measured voltage signals at SSSC location. The validation of results done in MATLAB environment.