A random forest-based approach for fault location detection in distribution systems

Finding the fault location in distribution network is difficult in comparison to transmission network based upon high branching and high impedances composed of the contact with environmental factors when a fault occurs. For this matter, the possible faulty section is identified and then the fault location is determined with the proposed algorithms in this study. Wavelet transform is applied to the current–voltage data along with feature extraction methods, and then, Random Forest is used for identifying the faulty section and estimating the fault location. To approve the validation, the algorithms are applied to IEEE-34 node test feeder. Single-phase to ground faults regarding different impedance values at different points of the feeder have been effectively detected by using single measurement point data from the sending end of the feeder.