Radial Basis Function Networks (RBFNs) are used for contingency evaluation
of bulk power system. The motivation behind this work is to exploit the non
-linear mapping capabilities of RBFNN in estimating line loading and bus vo
ltage of a bulk power system following a contingency. Unlike most of the av
ailable neural networks based techniques, the proposed method utilizes the
potential of RBFN in planning studies. The performance of the RBFN is compa
red with a standard AC load flow algorithm.