Contingency analysis of bulk power system using neural networks

Radial basis function networks (RBFNs) are used for the contingency evaluation of bulk power systems. The motivation behind this work is to exploit the nonlinear mapping capabilities of RBFN in estimating line loading and bus voltages of a bulk power system following a contingency. Unlike most of the available neural network-based techniques, the proposed method utilizes the potential of RBFN in planning studies. The performance of the RBFN is compared with a standard AC load flow algorith