Enhanced Transient Stability in Power Systems via Intelligent Control of SVCs Using Neural Networks

This paper investigates the application of Static VAR Compensators (SVCs) with neural network control to enhance power system grid stability, particularly in multi-source energy systems. SVCs, as Flexible alternating current Transmission Systems (FACTS) devices, are crucial for reactive power compensation and voltage regulation. The study models and simulates an SVC controlled by a neural network in MATLAB/Simulink, assessing its performance under three-phase fault conditions. The fault a 3-phase to-ground short circuit fault is introduced at location in close proximity to the wind energy sults demonstrate that the proposed control scheme effectively reduces system oscillations and improves dynamic response, leading to faster fault recovery and enhanced overall grid stability. The superior dynamic performance of the SVC-based neural network controller confirms its potential for improving power system resilience.