ARTIFICIAL NEURAL NETWORKS FOR ASSESSMENT POWER SYSTEM TRANSIENT STABILITY WITH TCVR

Abstract

This paper shows the modeling and the effectiveness of Thyristor Controlled Voltage Regulator (TCVR) for power systems transient stability improvement. Two applications of transient stability assessment are presented in this article: The first uses a Runge-Kutta method; the second application shows the effectiveness of artificial neural networks (ANNs) to calculate the CCT. Critical Clearing Time (CCT) is used as an index for evaluated transient stability. The effectiveness of the proposed methodology is tested in the WSCC3 nine-bus system in the case of three-phase short circuit fault on one transmission line. A simulation and comparison are presented in this document.