Fault location in a series compensated transmission line based on wavelet packet decomposition and support vector regression

This paper proposes a novel transmission line fault location scheme, combining wavelet packet decomposition (WPD) and support vector regression (SVR). Various types of faults at different locations, fault resistance and fault inception angles on a series compensated 400 kV–285.65 km power system transmission line are investigated. The system only utilizes a single-end measurements. WPD is used to extract distinctive fault features from 1/2 cycle of post fault signals after noises have been eliminated by a low pass filter, and SVR is trained with features obtained from WPD. After training, SVR was then used in precise location of fault on the transmission line. The result shows that fault location on transmission line can be determined rapidly and correctly irrespective of fault impedance.

► We modelled a series compensated power transmission line.
► We instantiated all short circuit faults at various fault inception angle and fault resistance.
► We extracted fault signatures from the phase current and voltages using the energy of Wavelet Packet Decomposition at level 3.
► We used Support vector regression for fault location based on a half cycle post fault data.