Combined S-transform and data-mining based intelligent micro-grid protection scheme

The paper presents a combined S-transform and decision tree based intelligent scheme for fault detection and classification in the micro-grid. The proposed method preprocesses the faulted current signals using S-transform to extract differential statistical features at the ends of the respective feeder, which are used to build decision tree based data-mining model for final relaying decision. One cycle post fault current samples of each phase from fault inception at bus-ends of the respective feeder are used to derive differential features. The differential features are used to train the three decision trees to provide fault detection, fault detection in different operating mode and fault class associated in the fault process. The algorithm is tested on simulated fault data with wide variations in operating parameters of the power system and the extensive test results indicate that the proposed intelligent relaying scheme can reliably provide protection measure for micro-grid with different modes of operation.