APPLICATION OF PMU AND FUZZY RADIAL BASIS FUNCTION NETWORK TO POWER SYSTEM TRANSIENT STABILITY PREDICTION

A new radial basis function network based on fuzzy clustering (FCRBFN) and its learning algorithm is proposed in this paper. The FCRBFN, whose inputs are simple function of generator rotor angles after fault measured by PMUs, is used to predict transient stability of multimachine power system. The numerical results of a real 49 machine power system demonstrate that the proposed method is effective to transient stability prediction with and without generator shedding, considering different operating conditions and fault locations. The learning process is considerable fast and the neural network have very high classification precision.