Estimation and Classification of Fault Using Wavelet Transforms and Radial Basis Function Neural Network (RBFNN)

This project describes the design and implementation of fault estimation and classification in the 33-bus transmission system consists of diesel power generator, wind generator, PV generator and hydro generator. The method proposed in this work is based on wavelet transforms and Radial Basis Function Neural Network (RBFNN). To verify the effectiveness of the strategy, a 33-bus microgrid test system operating in sequential and autonomous mode is proposed. The model with the proposed algorithm demonstrated relatively a short processing time and less computational complexity. The test system was designed and simulated in MATLAB programming interface for the design and testing of the proposed system.