Faulted Phase Selection Based on Wavelet Analysis of Traveling Waves

Abstract

Abstract-Accurate faulted phase selection is critical to avoid tripping of the incorrect phase or unnecessary three phase tripping. Moreover, an associated requirement of faulted phase selectors is high-speed operation, since the selection process must be completed in the immediate post-fault period before breaker opening. This paper presents a novel scheme for selecting a faulted phase on transmission line based on the traveling wave theory, meeting both the requirements of accuracy and speed. The proposed approach uses the mathematical tool of wavelet modulus maxima to solve the problem. MATLAB/ Simulink software was used to test the proposed faulted phase selection approach. Various fault conditions were simulated by varying fault type, fault resistance, fault location and fault inception angle, on a given power system model. The simulation results demonstrate the validity of the proposed approach of faulted phase selection.Index Terms-Faulted phase selection, traveling wave, wavelet modulus maxima, transmission line. I. INTRODUCTIONStatistically, about 80% of the faults on the transmission lines are transient in nature. These faults can disappear by themselves, if the supply is briefly interrupted and the arc path is allowed to de-ionize. Hence, auto-reclosing is attempted for the purpose of restoring transmission line to service subsequent to tripping of their associated circuit breaker due to faults [1]. Single pole auto-reclosure has long been recognized as an effective means of improving system security and reliability. Its benefits are particularly apparent in applications where economic and stability considerations preclude the use of three phase auto reclosure. Accurate faulted phase selection is required for implementation of such a scheme [2].Due to the limitations of the conventional methods, wide variety of faulted phase selection algorithms have been developed and proposed over the years to select the faulted phase(s combination of AI and non-AI techniques was used to identify the faulted phase(s) as in [7] and [8].Ref.[9] proposed faulted phase selection using wavelet transform based on the spectral energies of traveling waves. A fault classification scheme based on spectrum characteristics of traveling wave components obtained using FFT was given in [10]. Modal components of characteristics impedances were considered as fuzzy variables for identifying single line to ground and phase to phase faults [11]. Selection of faulted phase based on the wavelet analysis of modal components of traveling waves was presented in [12].However, the traveling wave based algorithms proposed were not supported by the results taking into account the effect of wide variation of uncontrolled fault parameters like fault inception angle and fault impedance. This paper presents a novel algorithm utilizing the fault parameters which are based on characteristics of wavelet modulus maxima of modal components of fault induced traveling waves. MATLAB/Simulink technical computing platform was used for offline simulation of w...

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