  The distance protection relays are used to determine the impedance based
fault location according to the current and voltage magnitudes in the
transmission lines. However, the fault location cannot be correctly detected in
mixed transmission lines due to different characteristic impedance per unit
length because the characteristic impedance of high voltage cable line is
significantly different from overhead line. Thus, determinations of the fault
section and location with the distance protection relays are difficult in the
mixed transmission lines. In this study, 154 kV overhead transmission line and
underground cable line are examined as the mixed transmission line for the
distance protection relays. Phase to ground faults are created in the mixed
transmission line. overhead line section and underground cable section are
simulated by using PSCAD-EMTDC.The short circuit fault images are generated in
the distance protection relay for the overhead transmission line and
underground cable transmission line faults. The images include the R-X
impedance diagram of the fault, and the R-X impedance diagram have been
detected by applying image processing steps. Artificial neural network (ANN)
and the regression methods are used for prediction of the fault location, and
the results of image processing are used as the input parameters for the
training process of ANN and the regression methods. The results of ANN and
regression methods are compared to select the most suitable method at the end
of this study for forecasting of the fault location in transmission lines.
