Voltage collapse prediction using artificial neural network

Unalleviated voltage instability frequently results in collapse; which is a cause of concern power system networks across the globe but particularly developing countries. This study proposed an online collapse prediction model through application machine learning technique and stability index called new line (NLSI_1). The approach based on multilayer feed-forward neural network whose inputs are variables NLSI_1. efficacy method was validated using testing IEEE 14-bus Nigeria 330-kV, 28-bus National Grid (NNG). simulations indicate that accurately predicted with R-value 0.9975 mean square error (MSE) 2.182415x10<sup>−5</sup> for 0.9989 MSE 1.2527x10<sup>−7</sup> NNG 28 bus system. presented this paper agree those found literature.