Online Estimation of Fault Location in Distribution Systems Based on Support Vector Machine from Wide Area Signals

This paper presents a new method for predicting fault location on distribution networks based on the support vector machine (SVM) technique. The proposed in an online non model based scheme which works based on the real data provided by wide area signals, performs as an intelligent indicator for online estimation of fault locations in distribution systems. In this case, for training intelligent SVM based indicator, a feature selection technique is used to find the best combination of the system phasor variables as input signal to the relay. For this purpose, several stable/unstable scenarios with the potential of oscillating dynamic behaviors are created by time domain transient stability simulation. The main merit of the proposed protection scheme is its ability for predicting instead of detection which can reasonably increase relay speed. The proposed approach is applied on IEEE 33-bus test system and the simulation results show promising performance for the SVM based relay.