Analysis and Detection of Power System Network Faults with Wavelet Transform

Abstract

Fault detection technique is important for enhancing protection, stability, reliability and continuity of supply. There are many fault detection techniques implemented in power system such as Fourier transform, wavelet transform, neural networks, etc. This research presents the fault identification and analysis using wavelet transform method as well as estimation of circuit breaker rating. The discrete wavelet transform is implemented for the fault identification in five bus system. Various types of line and ground faults have been considered and studied using Daubechies wavelet function. The first level decomposition is used for the fault analysis. The maximum detailed coefficients for various faults currents are analysed for the fault identification. The wavelet transform algorithm is implemented using MATLAB programming. The five-bus system is modelled in MATLAB Simulink and various faults are simulated. The switching time of fault is taken as 0.05 to 0.1 seconds. The faults have been studied at different points in the system. The fault identification method gives accurate results for different types of faults. The load flow analysis is also done for five bus system and appropriate rating of circuit breaker is estimated.