Abstract
It is necessary to detect the fault disturbances as quick as possible to improve performance of microgrid. Keeping an eye to the above issue this paper introduces a novel technique for the detection and classification of different faults in microgrid consisting of as Wind Turbine (WT), diesel generator, Solid Oxide Fuel Cell (SOFC) and micro-turbine. Wavelet transform (WT) and Wavelet Packet Transform (WPT) are used for detection and feature extraction to characterize the various faulted signals by using multi-resolution technique. Further, taking the input feature information of all fault disturbances, artificial neural network (ANN), neuro-fuzzy (NF) and Wavelet Neural Network (WNN) are implemented to accurately classify various faults. Two practically relevant 3-bus system and 14-bus microgrid system comprised with various types of distribution generations are considered for the protection analysis which is simulated using MATLAB/SIMULINK environment. Validation of the proposed technique has been done and compared with other two well proven and extensively used methods like ANN and NF under different operating scenarios.