Prediction of Transient Stability by a New Fuzzy Neural Network

The problem of transient stability and its aspects arc explained. Then application of a new fuzzy ncural network for prediction of transient stability, is described. This fuzzy neural network has a new hiter-Layer and Feed-Forward architecture ill which output of hidden nodes ire fuzzified. The proposed fuzzy neural network has Error Back-Propagation Learning (EBPL) algorithm as file training mechanic silt. This fuzzy neural network is applied for prediction of the transient stability status ill a disturbed power system The proposed fuzzy neural network has been tested oil lEEE 30 test system and a portion of frill's power network. Obtained results from these examinations confirm the validity of file developed approach. Also, a comparison between this fuzzy neural network and a Multi-Layer Perceptron with Error Back Propagation learning is presented. which indicates the efficiency of the proposed fuzzy neural network.